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Applied AI Architect, State and Local Government
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping state and local government agencies understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success - Support customers building with Claude Code, the Claude API, and Claude for Enterprise - Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel frequently to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have - Must have prior experience working with US federal, state, and/or local agencies - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager - Experience navigating complex buying cycles involving multiple stakeholders - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders - Experience designing scalable cloud architectures and integrating with enterprise systems - Familiar with Python - Familiarity with common LLM frameworks and tools or a background in machine learning or data science - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - A love of teaching, mentoring, and helping others succeed - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 - $345,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Applied AI Architect, Public Sector
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI team member at Anthropic, you will be a pre-sales architect focused on becoming a trusted technical advisor to the UK and Northern Europe public sector, with a primary focus on UK Central Government departments, executive agencies, and arm's length bodies, and a reach extending across devolved administrations, local government, the NHS, and Northern European public sector markets. This includes a growing focus on defence and national security, working with the MOD and intelligence agencies on some of the UK's most sensitive and mission-critical challenges. You will help these organisations understand the value of Claude and paint the vision for how they can successfully integrate and deploy Claude into their technology estates to modernise operations, improve policy delivery, and transform citizen services. You’ll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, Engineering, and Partnerships teams, you’ll guide customers from initial technical discovery through successful deployment. You’ll leverage your expertise to help customers understand Claude’s capabilities, develop evals, and design scalable, compliant architectures that maximise the value of our AI systems within the constraints that public sector organisations operate under. Responsibilities - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between departmental outcomes, policy objectives, and technical implementation. - Serve as the primary technical advisor to public sector customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams and stakeholders to drive customer success. - Support customers building with Claude Code, the Claude API, and Claude for Enterprise. - Create and deliver compelling technical content tailored to different audiences. You will need to span the gamut from technical deep dives for engineering and delivery teams up to business-value conversations with senior civil servants and C-suite executives (Permanent Secretaries, Directors General, SROs, CDIOs). - Support defence and national security engagements, including with the MOD and intelligence agencies, designing solutions that work within the security, classification, and accreditation constraints of these environments. - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack, with alignment to NCSC guidelines, Cyber Essentials Plus, the Government Security Classifications framework, the Technology Code of Practice, and the Service Standard. - Help customers develop evaluation frameworks to measure Claude’s performance for their specific use cases. - Identify common integration patterns across the UK public sector and contribute insights back to our Product and Engineering teams. - Travel frequently to customer sites across the UK (and occasionally Northern Europe) for workshops, technical deep dives, and relationship building. - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns. You may be a good fit if you have - Prior experience working with UK public sector organisations — particularly UK Central Government departments, executive agencies, or arm’s length bodies. - Active UK Security Check (SC) clearance, with willingness and eligibility to be put forward for higher levels of clearance (e.g. DV) where customer engagements require it. - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager. - Experience navigating complex public sector buying cycles involving multiple stakeholders — commercial teams, digital and technology leadership, policy owners, and SROs. - Familiarity with UK public procurement routes and frameworks is preferred — e.g. G-Cloud, the AI Dynamic Purchasing System (AI DPS), Digital Outcomes, and Crown Commercial Service agreements — and experience working with systems integrators and delivery partners within these frameworks. - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders, including senior civil servants, C-suite executives, engineering, and IT teams. - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders. - Experience designing scalable cloud architectures and integrating with enterprise systems. - Comfortable with Python. - Familiarity with common LLM frameworks and tools, or a background in machine learning or data science. - Excitement for engaging in cross-organisational collaboration, working through trade-offs, and balancing competing priorities. - A love of teaching, mentoring, and helping others succeed. - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £165,000 - £190,000 GBP Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Applied AI Architect, Industries
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success - Support customers building with both the Claude API and Claude for Work - Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel occasionally to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager - Native or C1 German and French speaker with fluent English proficiency - Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders - Experience designing scalable cloud architectures and integrating with enterprise systems - Comfortable with python - Familiarity with common LLM frameworks and tools or a background in machine learning or data science - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - A love of teaching, mentoring, and helping others succeed - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems Deadline to apply: None. Applications will be reviewed on a rolling basis. Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Applied AI Architect, Enterprise Tech
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success - Support customers building with both the Claude API and Claude for Work - Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel occasionally to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager - Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders - Experience designing scalable cloud architectures and integrating with enterprise systems - Comfortable with python - Familiarity with common LLM frameworks and tools or a background in machine learning or data science - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - A love of teaching, mentoring, and helping others succeed - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems Please note this role requires 3 days in office per week. Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 - $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Applied AI Architect, Applied AI (Digital Natives...
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success - Support customers building with both the Claude API and Claude for Work - Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel occasionally to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: - 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager - Native German speaker with fluent English proficiency - Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more - Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders - Experience designing scalable cloud architectures and integrating with enterprise systems - Comfortable with python - Familiarity with common LLM frameworks and tools or a background in machine learning or data science - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - A love of teaching, mentoring, and helping others succeed - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems Deadline to apply: None. Applications will be reviewed on a rolling basis. Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
[P] Data Engineer, Safeguards
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Data Engineer on the Safeguards team, you will build the data foundations that keep our AI systems safe. The Safeguards team works to monitor models, prevent misuse, and ensure user well-being — and doing that well requires robust, reliable data infrastructure. In this role, you will design and build the pipelines, warehousing solutions, and analytical tooling that power our safety and trust efforts at scale. You'll work closely with engineers, data scientists, and policy teams to ensure the Safeguards organization has the data it needs to detect abuse patterns, measure the effectiveness of safety interventions, and make informed decisions about model behavior and enforcement. This is a high-impact role where your work directly supports Anthropic's mission to develop AI that is safe and beneficial. Key responsibilities - Design, build, and maintain scalable data pipelines that support safety monitoring, abuse detection, and enforcement workflows - Develop and optimize data models and warehousing solutions to enable efficient analysis of large-scale usage and safety data - Build and maintain dashboards and reporting infrastructure that give Safeguards teams visibility into model behavior, misuse patterns, and enforcement outcomes - Collaborate with engineers to integrate data from multiple sources — including model outputs, user reports, and automated classifiers — into a unified analytical layer - Implement data quality frameworks, monitoring, and alerting to ensure the reliability of safety-critical data - Partner with research teams to surface data insights that inform model improvements and safety interventions - Develop self-service data tooling that enables stakeholders to explore safety data and generate reports independently - Contribute to data governance practices, including access controls, retention policies, and privacy-compliant data handling Minimum qualifications - Proficiency in SQL and Python, with hands-on experience building and maintaining ETL/ELT pipelines - Experience with cloud data platforms such as BigQuery, Redshift, Snowflake, or similar - Experience with modern data stack tools such as dbt, Airflow, Spark, or similar orchestration and transformation frameworks - Experience building dashboards and data visualizations using tools such as Looker, Tableau, or Metabase - Ability to communicate clearly and translate complex data concepts for both technical and non-technical audiences Preferred qualifications - 8+ years of experience in data engineering, analytics engineering, or a related role - Comfort contributing across the stack and picking up work outside your immediate scope when the situation calls for it - Background in trust and safety, integrity, fraud, or abuse detection data systems - Experience with large-scale event streaming systems such as Kafka, Pub/Sub, or Kinesis - Experience building data infrastructure that supports ML model monitoring or evaluation - Familiarity with data privacy and compliance frameworks such as GDPR, CCPA, or similar - Background in statistical analysis or experience working closely with data scientists - A genuine interest in the societal implications of AI and in making AI systems safer The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 - $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Product Manager, Safeguards Rare Harms
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is dedicated to developing AI assistants that are helpful, harmless, and honest. As usage of our AI services grows, we need to ensure they are not misused. The Safeguards team is at the forefront of protecting our users from the risks of powerful AIs as well as ethical, technical, and social risks from the use of generative AI. The Safeguards team at Anthropic builds protections for new AI features enabled by the research teams and protects new products and surfaces developed by our product teams. As a Product Manager for the Safeguards team at Anthropic, you will own the ideation, design, development and deployment of Safeguards systems and relevant product UX to ensure we are advancing frontier models safely to users across various cloud platforms. You will work closely with our research and product teams to develop detections, evals, interventions, and tools to measure and mitigate deployment and user risks. We are looking for a product manager who is deeply committed to making AI safe and beneficial for humanity. You are aware of the risks and are committed to working with experts and coming up with ideas for Anthropic to implement. You have deep technical expertise in development, deployment and measurement of Safeguards systems. You thrive in rapidly moving and ambiguous environments. Responsibilities: - Determine how to build in safety by design upstream and leverage downstream defenses for Anthropic’s frontier models, AI products, customers on different surfaces - Claude.ai, 1P API, external Cloud providers. - Ability to write safety evals and communicate externally about safety. - Drive impact via ruthless prioritization by clearly defining problems, solution options forward, clarity on both business & technical tradeoffs and accordingly clear requirements toward MVP vs. ideal state. - Align & collaborate with policy, enforcement, research, engineering and cross functional stakeholders. - Understand the AI landscape and ecosystem to plan for mitigation of deployment risks of increasingly powerful models and determined adversaries. - Lead the development of metrics to understand the area, performance, blindspots to help inform future project planning. You may be a good fit if you have: - 5+ years in product management with a focus on fast problem understanding, building roadmaps with tractable progress, ability to get into the details on data, detection & interventions, infrastructure & tools, and/or evals. - Ability to make technical tradeoff decisions; ideally with experience working across policy experts, AI/ML research engineers and software engineering teams to design and build state of the art safety systems. - Strong user understanding of how our products are used, their Safeguards concerns and how we provide the best solutions. - Demonstrated ability to build product and engineering strategy across multiple cross-functional teams for a rapidly changing space. - Demonstrated experience in designing and building metrics to evaluate risks, system performance, user impact and making crisp tradeoffs - Very strong ability to navigate, and prioritize amidst rapidly changing product specs, and to flex into different domains to bring clarity and execute. - Evidence of exercising judgment and decision making in ambiguous situations. - Planning, building, launching and measuring new products / systems in a zero to one environment. - Ability to clearly articulate complex technical concepts to non-technical audiences in written and verbal communication. - Think creatively about the risks and benefits of new technologies, and think beyond past checklists and playbooks. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $305,000 - $385,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Strategic Capture Lead, Homeland Security & Federa...
Scale is building AI for the world's most important decisions. In the homeland security and federal law enforcement space, that means the difference between a threat detected and a threat realized. A case closed or a criminal free. As a Strategic Capture Lead, you will identify, shape, and win the programs of record that bring Agentic AI to DHS, DOJ, and their components. You build the conditions that make Scale the only logical answer. What You'll Do - Own the Pursuit: Lead capture from pre-RFP shaping through award on high-value, multi-year programs across CBP, ICE, TSA, USCIS, CISA, FBI, DEA, ATF, and USMS. You set the strategy. We close the deal. - Shape the Mission: Engage SES-level and component leadership to influence requirements before they're written. Make the case for Agentic AI as mission infrastructure; not a pilot, not a tool, but the operating layer for enforcement, investigation, and threat response. - Architect the Team: Determine when Scale leads as Prime and when we anchor as a must-have sub. Negotiate the teaming agreements that win. - Bridge Capture to Execution: Partner with Deployment Strategists to transition awarded programs into funded, expanding accounts. What we promise in capture, we deliver in the field. - Navigate the Money: Map appropriations cycles, DHS/DOJ funding streams, and grant programs to protect and accelerate target opportunities. Who You Are You've spent 20+ years winning in the HS/LE market. You have programs of record on your track record, relationships at the component level, and a command of the acquisition landscape. You translate AI capability into mission outcomes. You don't pitch technology. You solve mission problems, and you know the difference. Requirements - 20+ years combined industry and BD/capture experience in DHS, DOJ, or Federal Law Enforcement markets - Proven wins on major Programs of Record or high-value task orders - Deep fluency in HS/LE acquisition vehicles and the FAR/DFARS/OTA landscape - Established relationships across DHS component leadership, DOJ/FBI senior ranks, and the prime contractor ecosystem - Technical literacy in AI/ML, data analytics, biometrics, or investigative intelligence platforms - Ability to travel up to 50% Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of Washington DC is: $203,200 - $254,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Staff Software Engineer, Data Platform
Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: - Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. - Collaborate with cross-functional teams to define, design, and deliver new features. - Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. - Present technical information to teams and stakeholders, providing guidance and insight on development processes and technologies. - Provide technical leadership, including: upholding and upleveling engineering standards across the organization, mentoring junior engineers. Ideally you’d have: - 8+ years of full-time engineering experience, post-graduation with specialties in back-end systems, specifically related to building large-scale data storage, streaming, and warehousing systems. - Extensive experience in various database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and various data query engines (Trino, Presto, Snowflake, etc.). - Show a track record of mentoring and leading teams in successful projects. - Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders. - Experience working fluently with standard containerization & deployment technologies like Kubernetes and various public cloud offerings. - Extensive experience in software development and a deep understanding of distributed systems, cloud platforms and data systems. - Experience driving cross functional collaboration and communication at an organizational or broader level. Nice to haves: - Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI). - Experience with performance tuning and cost optimizations of cloud based data platforms. - Experience defining a data lifecycle strategy and designing/implementing tooling for data privacy (i.e. GDPR) needs. - Experience scaling products at hyper-growth startups. - Excitement to work with AI technologies. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $252,000 - $315,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Software Engineer, Robotics & Autonomous Systems
Software Engineer - Robotics & Autonomous Systems Scale's Robotics business unit is dedicated to solving the data bottleneck in Physical AI across Robotics, Autonomous Vehicles, and Computer Vision. In this role, you'll be a key contributor building production systems for robotics data collection, model training pipelines, and evaluation infrastructure. You'll have the opportunity to own critical parts of our robotics platform, work directly with cutting-edge robotics and AV customers, and shape the future of embodied AI systems. You Will: - Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets - Build ML training and fine-tuning pipelines using Scale's robotics data - Work across backend (Python, Node.js , C++) and frontend (React, TypeScript) stacks to build end-to-end solutions - Develop tools and systems for robotics data collection, teleoperation, and model evaluation - Interact directly with robotics and AV stakeholders to understand their technical needs and drive product development - Build real-time systems for robotic control, sensor fusion, and perception pipelines - Design comprehensive monitoring and evaluation frameworks for robotics models and data quality - Collaborate with ML engineers and researchers to bring robotics research into production - Deliver features at high velocity while maintaining system reliability and performance Ideally, You Have: - 3+ years of software engineering experience in robotics, autonomous vehicles, or related fields - Strong programming skills in Python and TypeScript/Node.js for production systems - Experience with React and modern frontend development for 3D interfaces - Practical experience with robotics frameworks (ROS/ROS2), simulation environments, or AV systems - Understanding of distributed systems, workflow orchestration, and cloud infrastructure (AWS, Temporal, Kubernetes, Docker) - Experience with databases (MongoDB, PostgreSQL) and data processing at scale - Track record of working with cross-functional teams including ML engineers, researchers, and customers - Strong communication skills and ability to operate with high autonomy Nice to Haves: - Experience with C++ - Experience with robotics hardware platforms (robotic arms, mobile robots, perception systems) with a focus on time synchronization - Background in computer vision, SLAM, motion planning, or imitation learning - Familiarity with autonomous vehicle data, lidar technologies, or 3D data processing - Experience with ML model deployment and serving frameworks - Knowledge of teleoperation systems (ALOHA, UMI, hand tracking) or VR interfaces - Experience with workflow orchestration systems (Temporal, Airflow) - Published research or open-source contributions in robotics or autonomous systems Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of San Francisco is: $180,000 - $225,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Software Engineer, Platform
Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: - Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. - Collaborating with cross-functional teams to define, design, and deliver new features. - Proactively identifying opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. - Presenting technical information to teams and stakeholders, providing guidance and insight on development processes and technologies. Ideally you’d have: - 3+ years of full-time engineering experience, post-graduation with specialities in back-end systems. - Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS preferred). - Show a track record of independent ownership of successful engineering projects. - Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders. - Experience working fluently with standard containerization & deployment technologies like Kubernetes, Terraform, Docker, etc. - Experience with orchestration platforms, such as Temporal and AWS Step Functions. - Experience with NoSQL document databases (MongoDB) and structured databases (Postgres). - Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI). Nice to haves: - Experience with data warehouses (Snowflake, Firebolt) and data pipeline/ETL tools (Dagster, dbt). - Experience with authentication/authorization systems (Zanzibar, Authz, etc.) - Experience scaling products at hyper-growth startups. - Excitement to work with AI technologies. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of San Francisco is: $216,000 - $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Senior Software Engineer - Agentic Tooling & Produ...
Scale AI is hiring a highly skilled Senior Software Engineer to help design, build, and operate secure, scalable infrastructure that empowers our employees to do their best work. You’ll join a creative, fast-moving, solutions-oriented group that architects and implements automation across identity and access management, endpoint management, and our broader SaaS stack. The ideal candidate will leverage various in-house and external models/platforms to build applications, slackbots, and dashboards for internal users, and streamline complex workflows through automation. This role will play a major role in elevating the overall velocity of all G&A teams at the organization. The Impact You Will Have - As a full stack engineer (60% BE / 40% FE), you will work with your team to build amazing tools/applications for internal company use as well as external customers/partners - You will design, develop, test, and support full-stack applications on cloud-native distributed systems - You will build real-time integrations with SaaS platforms across the organization - You will build a quality framework/unit tests that ensure product quality, performance, and load and are able to debug/identify system issues - You will collaborate with the broader teams, engage in engineering council, conduct code reviews, and improve our delivery process - Collaborate with the IAM team to manage cloud-based identity (Okta) and access controls, ensuring compliance with security policies and standards for internal applications. - Work heavily cross-functionally to identify areas for corporate technology service improvement and implement self-service solutions. What We Look For - 5+ years of related experience with a Bachelor’s degree; or equivalent work experience. - Proficiency with UI frameworks such as React or Angular and HTML, CSS, Typescript, etc - Proficiency with backend technologies, including API development, databases, and privacy permissions. Ex. Go, Python, PostgreSQL and GraphQL - Experience with end-to-end testing and documentation - Experience developing secure, scalable, and resilient applications on the cloud that handle sensitive data - Experience with cloud technologies, e.g., AWS, Azure, GCP, Docker, or Kubernetes - Familiarity with compliance frameworks such as SOC 2, ISO 27001, FedRAMP, and NIST. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of San Francisco is: $216,000 - $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Senior AI Product Manager, Healthcare Agents
Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world’s most important decisions. We’re looking for an AI Product Manager to own the Healthcare vertical within our Agents Data & Reinforcement Learning Environments team. In this role, you’ll own both the development of RL environments (the realistic, high-fidelity simulations of healthcare software and workflows that labs use to train and evaluate agents) and the “data as a product” strategy that powers them. You’ll understand where AI is being used in the Healthcare industry, decide what healthcare tasks are worth modeling, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside the Healthcare industry, and is able to pair that domain understanding with a sense for AI research and current agent capabilities in Healthcare workflows. You’ll translate that expertise into environments and datasets that teach AI agents to perform real healthcare work, and you’ll be the domain expert Scale’s most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You’ll Do - Own the Healthcare AI roadmap & data strategy: Set product direction for the Healthcare agents training stack and the data strategy behind it. Establish a vision for where AI is continuing to transform the Healthcare industry, driving execution across engineering, operations, and go-to-market teams. - Build partnerships with research teams at frontier labs: Work directly with researchers at leading AI labs to understand where their Healthcare agentic capabilities fall short and shape new product lines and competitive strategy for the vertical. Connect with AI startups and industry leaders to launch joint benchmarks and build Scale’s brand in Healthcare. - Design and scale Healthcare-specific environments: Scope and build simulations of real Healthcare workflows and environments that let labs train and evaluate agents against real world scenarios. Partner with ML and Operations to translate the judgement, edge cases, and workflows you know from the industry into high quality training products. - Collaborate cross-functionally — influence business priorities and dive into the weeds of research, operations, and customer interactions to deliver mission-critical outcomes. Ideally, You’d Have - 2–4 years of direct experience in the Healthcare industry in one or more of: healthcare research, clinicians & clinical staff using EHRs daily, revenue cycle management, or a healthtech product role, with real depth in how the work gets done. - AI-Forward Thinking : Quick to adopt AI solutions to streamline your day-to-day workflows and an ability to understand and articulate how it’s transforming your industry. - A builder’s mindset: excited by ambiguity and motivated to create new products from the ground up. - Product or customer-facing experience: A track record of owning outcomes, shaping roadmaps, or working closely with technical stakeholders (formal PM experience is a plus but not required if domain depth is strong). - ML Intuition & Technical Fluency: Enough intuition around how model training and evaluation works and what a Reinforcement Learning environment looks like. A software background is a plus. - Bias for action: Comfort wearing multiple hats and operating in fast-moving environments. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $205,600 - $257,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Senior AI Product Manager, Finance Agents
Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world’s most important decisions. We’re looking for an AI Product Manager to own the Finance vertical within our Agents Data & Reinforcement Learning Environments team. In this role, you’ll own both the development of RL environments (the realistic, high-fidelity simulations of financial software and workflows that labs use to train and evaluate agents) and the “data as a product” strategy that powers them. You’ll understand where AI is being used in the Finance industry, decide what financial tasks are worth modeling, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside the Finance industry, and is able to pair that domain understanding with a sense for AI research and current agent capabilities in Finance workflows. You’ll translate that expertise into environments and datasets that teach AI agents to perform real financial work, and you’ll be the domain expert Scale’s most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You’ll Do - Own the Finance AI roadmap & data strategy: Set product direction for the Finance agents training stack and the data strategy behind it. Establish a vision for where AI is continuing to transform the Finance industry (including investment banking, private equity, public markets, corporate finance, FP&A, etc), driving execution across engineering, operations, and go-to-market teams. - Build partnerships with research teams at frontier labs: Work directly with researchers at leading AI labs to understand where their Finance agentic capabilities fall short and shape new product lines and competitive strategy for the vertical. Connect with AI startups and industry leaders to launch joint benchmarks and build Scale’s brand in Finance. - Design and scale Finance-specific environments: Scope and build simulations of real Finance workflows and environments (financial models, investment memos, forecasts, dashboards, data rooms, etc) that let labs train and evaluate agents against real world scenarios. Partner with ML and Operations to translate the judgement, edge cases, and workflows you know from the industry into high quality training products. - Collaborate cross-functionally — influence business priorities and dive into the weeds of research, operations, and customer interactions to deliver mission-critical outcomes. Ideally, You’d Have - 3–6 years of direct experience in the Finance industry in one or more of: investment banking, private equity, trading, asset or portfolio management, strategic finance, corp dev, or a fintech product role, with real depth in how the work gets done. - AI-Forward Thinking : Quick to adopt AI solutions to streamline your day-to-day workflows and an ability to understand and articulate how it’s transforming your industry. - A builder’s mindset: excited by ambiguity and motivated to create new products from the ground up. - Product or customer-facing experience: A track record of owning outcomes, shaping roadmaps, or working closely with technical stakeholders (formal PM experience is a plus but not required if domain depth is strong). - ML Intuition & Technical Fluency: Enough intuition around how model training and evaluation works and what a Reinforcement Learning environment looks like. A software background is a plus. - Bias for action: Comfort wearing multiple hats and operating in fast-moving environments. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $205,000 - $257,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Safety Coordinator / Lab Lead
At Scale, we believe that the next frontier of artificial intelligence is embodied. The Physical AI team is focused on building general AI that can reason and act in the physical world. By leveraging Scale’s massive, industry-leading data infrastructure, we are partnering with frontier labs to build Foundation Models for Physical AI that will redefine the future of automation. To support our rapid hardware-software iteration cycles and ensure a world-class R&D environment, we are looking for a Safety Coordinator / Lab Lead to anchor our physical testing operations. Role Overview As the Safety Coordinator / Lab Lead , you will play a mission-critical role in scaling our physical testing infrastructure safely and efficiently. This is a high-impact position where your highest-priority responsibility will be owning the end-to-end execution of safety audits and incident documentation . Operating at the intersection of cutting-edge AI foundation models and complex robotics hardware, you will ensure our researchers, engineers, and autonomous systems interact in a secure, compliant, and highly organized environment. Core Responsibilities Priority Focus: Safety Audits & Incident Documentation - Rigorous Safety Audits: Design, schedule, and execute routine safety audits across all physical testing environments, robot cells, and hardware workspaces to ensure continuous compliance with internal benchmarks and industrial safety standards. - Incident & Near-Miss Documentation: Own the end-to-end incident management pipeline. Act as the primary point of contact for documenting, archiving, and analyzing any lab incidents, mechanical anomalies, or near-misses. - Root-Cause Analysis (RCA): Lead structured post-incident investigations to identify systematic risks, authoring comprehensive RCA reports and implementing Corrective and Preventive Actions (CAPA). - Data-Driven Risk Mitigation: Treat safety data as a core operational asset—tracking safety metrics and audit trends to proactively surface and mitigate physical, electrical, and battery-related hazards. - Cross-functional standardization & accountability: Build the tools/processes and associated documentation to drive standardization regarding safe work practices across all multiple facilities. Build mechanisms to hold all employees and partners to a high bar for safety in any Robotics facility. Lab Leadership & Operational Excellence - Daily Lab Operations: Manage the layout, organization, and upkeep of our physical testing arenas and motion-capture volumes using 5S or equivalent workplace organization methodologies. - Hardware & Asset Management: Oversee the inventory, calibration, and maintenance of specialized robotics hardware, compute nodes, and safety gear (PPE). - Cross-Functional Coordination: Collaborate closely with hardware and software engineering teams to smoothly manage workspace allocation for concurrent foundation model testing tracks. Safety Culture & Onboarding - Onboarding & Compliance: Develop, update, and deliver mandatory safety onboarding modules for all incoming engineers, researchers, and partners. - Culture Champion: Cultivate a proactive, "safety-first" culture that matches the velocity of Scale's rapid AI development without compromising on physical guardrails. Qualifications & Experience Requirements - Experience: 3+ years of experience in lab management, safety coordination, or technical operations within a high-velocity robotics, aerospace, automotive, or autonomous vehicle R&D environment. - Safety Protocols: Demonstrated experience building out structured audit workflows and detailed incident documentation pipelines (familiarity with OSHA standards or ISO robotics safety standards is highly valued). - Technical Comfort: Ability to seamlessly navigate an environment featuring complex physical hardware, multi-modal sensors, and advanced compute rigs. - Communication & Drive: Exceptional written communication skills for documentation, with the assertive communication style required to enforce safety protocols across a brilliant, fast-moving engineering team. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of San Francisco is: $134,400 - $168,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Quality Lead
Scale is looking for a Quality Lead to ensure top-tier data quality across our Generative AI programs. In this role, you will partner directly with Scale’s Delivery teams to ensure that the Quality Team’s core operation runs smoothly and that only high-quality data is delivered to our customers. You will: - Lead and develop teams of quality control auditors. - Partner with delivery teams to interpret and improve customer requirements. - Oversee day-to-day operations, including workload allocation and reporting insights. - Establish and uphold scalable best practices. - Drive initiatives that improve quality, efficiency, and customer satisfaction. Ideally you'd have: - A Bachelor’s degree in Computer Science, Engineering, Operations, or a related field. - 2+ years improving operational/technical processes. - Strong analytical and problem-solving skills (particularly in SQL and Google Sheets / Excel) with attention to detail. - Experience building systems and processes - A hands-on background in product management, software development, or top-tier management consulting. - Proven experience taking initiative in cross-functional technical environments. Nice to haves: - Master’s degree in Computer Science, Engineering, Operations, or a related field. - A hands-on background in quality assurance - Experience in AI/ML services. - Experience in a fast-growing, less-structured startup environment. - Experience building teams from the ground up. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $109,600 - $137,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Product Marketing Lead, GenAI
At Scale, we develop reliable AI systems for the world’s most important decisions. Scale’s product marketing team is responsible for developing and executing strategies that drive awareness and adoption for Scale’s offering. We understand our customers’ needs and challenges and ensure that their voices are reflected in product development and messaging. We then partner closely with product, engineering, research, sales, comms, and the broader marketing team to create a cohesive customer experience across all our channels. This role sits at the center of Scale’s GenAI data products, which power the world’s leading AI labs. As one of the largest providers of high-quality AI training data, we’ve built our reputation on speed, quality, frontier research, and a growing suite of multimodal data capabilities. The market is evolving fast, and we’re looking for a marketer who can go on offense to sharpen our narrative and build a playbook that earns the trust of the AI community. The ideal candidate combines strategic thinking with hands-on execution. You will: - Own positioning and messaging for Scale’s GenAI data products, articulating our differentiation on data quality, delivery speed, and multimodal breadth in a way that resonates with AI researchers and technical buyers. - Lead the content and social strategy for Scale Labs ’ dedicated online presence, taking a research-native approach that earns attention and credibility from the AI community. - Build and maintain competitive intelligence and a sharp point of view on the data market, arming the team with differentiated positioning as the market evolves. - Partner with Scale Labs researchers to amplify published work - leaderboards, benchmarks, and research papers - and translate it into pipeline and demand generation for the GenAI business - Develop go-to-market strategies for new data offerings and modalities, working closely with product and sales to drive awareness and build market momentum. - Collaborate cross-functionally with sales, engineering, and research to ensure consistent, compelling messaging across every customer touchpoint. Ideally, you’d have: - 5+ years of experience in product marketing, with a track record of marketing technical products to developer or research audiences. - Strong technical fluency and passion for AI. You can hold a credible conversation about AI/ML fundamentals, training, and the role of data quality in model performance. - Experience building social-native content and community strategies on platforms like X, with an instinct for what resonates with technical practitioners - Excellent written communication and storytelling skills — you can make complex technical concepts compelling without oversimplifying them. - Ability to work across functions and move fast in a dynamic, high-stakes environment. Nice to haves: - Familiarity with the AI training data market, or adjacent data and infrastructure spaces. - An existing network or relationships within the AI research community. - Experience navigating competitive markets where differentiation requires more than feature comparisons. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of San Francisco is: $155,200 - $194,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Product Manager, Gen AI
Scale AI builds the data infrastructure that powers the world’s most advanced AI. We are the trusted data partner behind frontier model makers and enterprise AI teams — providing the high-quality training data, evaluation frameworks, and human-feedback systems that make models smarter, safer, and more capable. Scale operates as a two-sided marketplace. On the demand side , our customers — leading AI labs and enterprises — need precisely labeled, expert-curated data to train and evaluate their models. On the supply side , we work with a global network of 500,000+ skilled contributors across 100+ countries who perform the complex annotation, evaluation, and data-generation tasks that fuel AI progress. Product Managers at Scale sit at the intersection of these two sides, shaping the systems, tooling, and experiences that make this marketplace work at unprecedented quality and scale. We are hiring Product Managers across multiple teams within our GenAI organization. These roles span both demand-side products (the tools and platforms our customers interact with) and supply-side products (the systems that power our contributor ecosystem). Each role offers the opportunity to work on high-impact, technically complex problems at the frontier of AI — with dedicated engineering, design, and data science teams. About the Role - Scale’s GenAI platform is how the world’s leading AI companies — from frontier model labs to Fortune 500 enterprises — create the training data that makes their models best-in-class. As a PM here, you are building the systems that directly shape AI model quality. - These roles are deeply cross-functional. You will work with dedicated engineering, design, and data science teams, as well as operations, finance, growth, and customer-facing stakeholders. The problems are technically complex, the pace is fast, and the impact is measurable. - Whether you are on the demand side (shaping the products customers use to create and evaluate training data) or the supply side (building the systems that power our global contributor marketplace), you will own your product area end-to-end — from strategy to execution to instrumentation. - Scale is a growth-stage company with the resources of a well-funded leader and the urgency of a startup. PMs here operate with significant autonomy, ship frequently, and are expected to be deeply analytical and hands-on. Example Product Management Openings: Task UX (Demand Side) — Own the end-to-end tasking product. You will define how tasks are designed, how contributors interact with multi-turn chat interfaces, and how in-task quality is measured and enforced across diverse conversational modalities. This is a critical surface area for training the next generation of models. Multi-Dimensional Quality (Demand Side) — Own Scale’s MDQ measurement framework, the CoPilot assisted-annotation experience, and our data pipeline connectivity layer. You will drive the core data quality infrastructure that customers depend on — defining how quality is decomposed, measured, and surfaced, while building AI-assisted tooling that helps contributors produce higher-quality outputs faster. Pay & Incentives (Supply Side) — This PM owns the payment and incentive systems that serve Scale’s global contributor base. You will ensure 500,000+ contributors across 100+ countries are paid accurately and on time, set pay rates methodically by skill and geography, and design incentive structures that balance cost efficiency, data quality, and contributor satisfaction. This role sits at the intersection of marketplace economics, global payments operations, and contributor experience. You Will - Set the product strategy and roadmap for your area, grounded in customer needs, data analysis, and business impact - Develop and execute a data-driven product roadmap through close collaboration with senior leadership, engineering, operations, data science, analytics, and design - Translate customer and internal-user needs into clear, well-defined functional and technical requirements backed by data analysis and deep understanding of your users - Guide and interface closely with engineering and data teams to define scope, review and refine technical capabilities, prioritize projects for release, and identify new opportunities - Build long-term instrumentation, monitoring, and evaluation capabilities for product performance tracking and insight generation - Establish business cases and projected return on investment to identify and prioritize opportunities - Partner with finance and business leaders to manage impact on the profitability and growth of the overall business - Communicate product vision, strategy, and progress to executive stakeholders and cross-functional partners Ideally, You’d Have - 4–10 years of experience in Product Management in the tech industry, with scope appropriate to level (L4: 4–6 yrs, L5: 6–8 yrs, L6: 8–10+ yrs) - Strong business acumen and analytical rigor, with demonstrated success driving products in ambiguous, high-growth environments - Experience translating complex technical systems into clear product strategies — comfort engaging deeply with engineering and data science teams - Excellent communication and stakeholder management skills, capable of influencing across technical and non-technical audiences - Experience building products from the ground up and iterating through the scaling journey of a business - Bachelor’s or advanced degree in a quantitative, engineering, or related discipline Nice to Have: - Experience in AI/ML, data infrastructure, or marketplace businesses - Strong understanding of the AI landscape — model training workflows, data labeling, evaluation, and deployment - Experience with global payment systems, contributor/gig-economy platforms, or trust & safety domains - Experience working at high-growth startups or scaling consumer/enterprise platforms Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $205,600 - $257,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Product Manager, Enterprise Core Platform
Role Summary Scale is building the agentic operating system that powers AI deployment across the world's most important organizations. The Platform PM is the person who determines what that foundation needs to be — and holds the bar on how well it gets built. This is not a roadmap PM, a program manager, or a feature tracker. The Platform PM owns the core infrastructure that every FD team builds on top of: defining the foundation before anything else can be built reliably, sequencing work against real customer commitments and FD team velocity, identifying which FD-built patterns are ready to graduate to core, and ensuring that every capability that ships does so at a bar customers can trust without thinking about it. The best Platform PMs have defined platform capabilities at production bar in high-stakes environments and understand the difference between what is necessary to build, what is interesting to build, and what should never be built at all. What You'll Do - Define the foundation. Determine what needs to be true at the core platform layer — across each capability pillar — before anything reliable can be built on top of it. - Sequence it. Prioritize and order platform work given customer commitments, FD team velocity needs, and what is actually blocking progress today. Getting this wrong means building on an unstable base or building the right things in the wrong order and paying for it in rework and FD team drag. - Identify patterns and graduate capabilities. Watch what FD teams are building across the application layer, determine what is genuinely repeating, and make the call on what moves to core — and when. Do not rush graduation or delay it out of caution. - Hold the quality bar. Every capability on the platform roadmap earns its place twice: once by being necessary, and again by being done well enough that customers trust it without thinking about it. Keep the platform from becoming a graveyard of half-built capabilities. - Unlock delivery team time to value. Forward deployed delivery teams should spend their time solving the hardest customer problems, not rebuilding plumbing on every engagement. That requires a platform that is secure by default, deployable anywhere, observable in production, and equipped with the agentic primitives, eval infrastructure, expert judgment capture, and data reasoning capabilities that every agent workload needs. - Partner across the organization. Work closely with platform engineering, forward deployed PMs, and BU leads to surface signal, resolve sequencing tradeoffs, and keep the roadmap grounded in what is actually blocking work. What We're Looking For Must-Have Qualifications - 6+ years in product management with meaningful time owning platform, infrastructure, or developer-facing products at production bar. - Demonstrated record of defining and shipping platform capabilities — not features on top of a platform someone else built. You can describe the architectural decisions you made, what production required, and what you learned. - Strong sequencing judgment: can prioritize across competing customer commitments and team velocity needs with incomplete information, without thrashing. - Technical fluency sufficient to hold real conversations with platform engineers about architectural tradeoffs across infra, auth, observability, deployment, and agent runtime. Not deep coding, but genuine comprehension of how production systems work. - Extreme ownership and follow-through: closes loops without reminders, drives outcomes across teams without formal authority, holds self and others to commitments. - Clear, precise communication: adjusts for audience (platform engineer vs. FD PM vs. executive); writes and speaks at the right level of detail. Core Competencies - Platform foundation ownership: has defined what a platform capability needs to be before it can be used reliably in production; understands what 'done' means at the platform layer vs. the application layer. - Sequencing and prioritization judgment: sequences work against real customer commitments and FD team velocity needs — not what is technically interesting or easiest to build. - Pattern recognition: identifies when field-built work has genuinely repeated and is ready to graduate to core; does not rush graduation or delay it out of caution. - Quality discipline: every capability earns its place twice — by being necessary and by being done well enough that it is trusted without thinking about it. - Cross-functional influence: drives field teams and platform engineering toward shared outcomes through evidence and framing, not process. - Operating in ambiguity: creates structure where there is none; makes sequencing calls with incomplete information; does not wait for fully-formed requirements. Nice-to-Haves - Direct experience with AI/ML platform infrastructure — agent frameworks, eval pipelines, fine-tuning workflows, or observability for production AI systems. - Experience deploying into constrained environments: government, regulated industries, air-gapped or classified infrastructure. - Prior experience as a platform or infrastructure PM at a company where field-built patterns were a key signal source for the core product. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $205,600 - $300,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
National Security Hackathon 2026 - General Interes...
National Security Hackathon Attendees – Stay Connected with Scale AI This posting is for candidates who attended National Security Hackathon and connected with a member of the Scale AI team. It was great meeting you at the Hackathon! Whether we spoke at our booth or on the floor, we always enjoy connecting with people who are passionate about advancing AI and machine learning. At Scale AI, our mission is to develop reliable AI systems for the world's most important decisions. For the past ten years, Scale has been the leading AI data foundry, supporting some of the most exciting advancements in AI, including generative AI, defense applications, robotics, and autonomous systems. We’re continuing to grow our team across a range of technical and mission-focused roles. If you're excited about the problems we’re tackling, feel free to share your information here. A member of our team will reach out if there’s a strong fit with one of our open opportunities. And even if the timing isn’t right today, we’d love to stay connected. We look forward to continuing the conversation. In the meantime, you can learn more about our work at scale.com . Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $227,200 - $284,000 USD Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of Washington DC, Texas, Colorado, Hawaii is: $204,800 - $256,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Head of Healthcare GTM
Head of Healthcare and Life Sciences GTM AI is transforming how the world’s largest companies operate. At Scale, our mission is to Develop reliable AI systems for the world’s most important decisions. Scale has powered breakthroughs in generative AI, defense, and autonomy. Following our Series F, we’ve continued doubling down on accelerating Fortune 100 enterprises' build and deploy AI agents that solve complex, real-world problems - through our Scale Generative AI Platform (SGP). About the Role We’re looking for a senior leader to own and scale our go-to-market strategy for the Healthcare industry. This person will combine deep industry expertise with strategic sales and partnership skills to define how we bring our generative AI, data, and software solutions to market within the vertical. The ideal candidate will have a mix of consulting, sales, and business development experience — capable of shaping a GTM playbook from the ground up, leading strategic accounts, and building a partner ecosystem that accelerates growth. This is a chance to own a vertical from zero to scale, define the GTM playbook, and shape how generative AI transforms Healthcare globally. Key Responsibilities Vertical GTM Strategy - Define and execute the GTM strategy for the Healthcare industry, including segmentation, messaging, pricing, and channel approach. - Identify and prioritize high-value use cases that align with industry pain points and regulatory realities. - Develop scalable playbooks for account targeting, value messaging, and proof-of-value delivery. Sales Leadership - Own pipeline generation and revenue targets for the Healthcare vertical. - Lead complex and large enterprise deals end-to-end — from discovery and value mapping through close and expansion. - Build and maintain executive relationships with key industry customers (CIO, CTO, CDO, COO, or line-of-business heads). - Partner with pre-sales and delivery teams to ensure successful implementations and reference outcomes. Partnerships & Ecosystem - Establish strategic partnerships with consulting firms, SIs, and technology vendors relevant to Healthcare. - Drive joint GTM programs, co-sell opportunities, and co-delivery engagements. - Develop alliances that help scale reach, credibility, and execution capacity. Cross-Functional Collaboration - Partner with Product to translate customer needs into roadmap priorities and solution blueprints. - Collaborate with Marketing on industry-specific campaigns, content, and events. - Align closely with Delivery to ensure customer success and repeatable outcomes. Leadership & Scale - Recruit and develop a vertical GTM team as the business grows. - Represent the company at key industry forums, conferences, and executive roundtables. - Build a strong internal knowledge base around Healthcare workflows, compliance, and trends. Ideal Candidate Experience - 10+ years in enterprise sales, GTM, or strategy roles within Healthcare or selling into it. - Track record of closing complex, multi-stakeholder enterprise deals ($1M+). - Strong familiarity with data, AI, or digital transformation initiatives in the industry. - Experience building or scaling a vertical practice within a consulting, SaaS, or data/AI company. - Proven ability to work with partners and ecosystem players to co-create market presence. Skills & Attributes - Strategic mindset: able to build a market plan and execute tactically. - Consultative approach with ability to translate technology into business outcomes. - Deep empathy for industry-specific pain points and decision-making dynamics. - Excellent communication, executive presence, and influencing skills. - Comfortable in high-velocity, ambiguous, fast-scaling environments. Success Metrics - Vertical revenue and pipeline growth. - Number and quality of reference customers. - Partner-sourced and co-sold pipeline. - Expansion within existing accounts. - Repeatable GTM plays launched and scaled. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco and New York is: $210,000 - $262,500 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Head of Global Assurance
Scale seeks a Head of Global Assurance to lead a high-performing team of technical experts advancing Scale’s assurance programs across its Global Public Sector and Commercial business units. This is a leadership role for an experienced assurance, cybersecurity compliance, or GRC professional who can manage a team of senior technical experts, drive execution across complex government and customer requirements, and partner closely with Global Public Sector, Enterprise, Security, Engineering, Product, and the Legal team. You Will - Lead assurance programs across Scale’s Global Public Sector and Commercial businesses, including FedRAMP, NIST frameworks, SOC 2, ISO 27001, and other customer, regulatory, and business assurance requirements. - Manage and develop a technical assurance team responsible for public sector authorizations, commercial assurance, audits, customer commitments, control evidence, remediation, and reporting. - Set priorities and operating cadences for assurance workflows, including intake, evidence collection, control owner follow-up, remediation tracking, metrics, and deadline management. - Build the metrics, dashboards, and reporting cadences that give company leadership a clear view of program health, key risks, and strategic priorities. - Partner with Legal on contract-driven assurance obligations, sensitive escalations, external-facing responses, and customer-facing representation issues. - Work closely with Global Public Sector, Enterprise, Security, Engineering, Product, and other control owners to validate evidence, track remediation, and support authorization and audit requirements. - Collaborate across Legal and GRC on a unified controls framework for security and other regulatory requirements. - Manage relationships with external auditors, assessors, and certification bodies. Ideally, You’d Have - 10+ years of experience in cybersecurity compliance, GRC, public and commercial sector assurance, IT audit, cloud security, or related roles. - Active U.S. security clearance, SCI eligible. - Experience leading global or region-specific assurance programs through scalable control frameworks and cross-functional execution. - Experience managing senior technical assurance, cybersecurity compliance, GRC, audit, or control evidence professionals. - Experience managing distributed teams across time zones. - Deep familiarity with FedRAMP, continuous monitoring, authorization packages, and related NIST frameworks. - Experience leading customer assurance, control evidence, remediation, reporting, and audit workflows. - Experience overseeing SOC 2, ISO 27001, and other commercial assurance frameworks. - Experience with external assessors, authorizing officials, government customers, public sector partners, commercial auditors, or certification bodies. - Experience working with legal teams on contract-driven assurance obligations, and strong judgment on when to escalate legal, contractual, technical, security, customer-facing, or privileged issues. - Excellent communication skills, including the ability to explain technical assurance issues clearly to legal, business, security, and executive audiences. - Experience developing compliance or assurance approaches for emerging technologies, including GenAI, AI/ML, data platforms, or cloud infrastructure. - Experience advising leadership on assurance, compliance, and risk tradeoffs in fast-moving technical environments. - Experience with defense, federal civilian, classified, national security, GovCloud, or JAB authorization environments. - Ability to translate new or ambiguous technical issues into practical compliance controls and implementation plans. Nice to Have - Relevant certifications such as CISSP, CISM, CISA, CCSP, AWS Certified Solutions Architect, Azure Solutions Architect, or similar credentials. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $287,200 - $359,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Head of Finance Systems & Automation
About the Role The Head of Financial Systems will own the strategy, implementation, and continuous improvement of Scale AI's finance technology stack. You are a builder-first leader who blends enterprise architecture with AI automation - eliminating manual workflows, tightening the financial data fabric, and enabling the Finance team to move with the speed and rigor the business demands. You will be the primary technology partner to the Finance leadership team, and the person ultimately accountable for the reliability, scalability, and intelligence of every system that touches the financial close, revenue, and spend lifecycle. Key Responsibilities ERP Ownership & Optimization Own the full lifecycle of our ERP environment (NetSuite or equivalent), including architecture, configuration, integrations, and roadmap. Ensure the platform reliably supports the General Ledger, AP, AR, Procure-to-Pay, Fixed Assets, Revenue Recognition, Sales Audit, and International Consolidations & Reporting. Order-to-Cash & Procure-to-Pay Drive end-to-end process excellence across Order-to-Cash (Sales/Revenue Capture, Sales Audit, Billing) and Procure-to-Pay (Direct & Indirect Purchasing). Identify gaps between upstream systems and ERP, and close them through disciplined integration design. AI Agent Deployment Identify opportunities to replace manual finance workflows with AI/LLM-powered agents. Build and manage internal agents that automate forecasting inputs, variance analysis, close task management, and reconciliation — reducing cycle time and surfacing actionable insights for Finance leadership. Systems Integration & Data Architecture Design scalable data flows and APIs that connect the ERP to adjacent finance tools (billing, expense, FP&A, treasury) into a cohesive, auditable ecosystem. Ensure clean, governed data movement from source systems to the general ledger and reporting layer. Operational Excellence & Controls Establish disciplined change management, clear data governance, and measurable SLAs across all financial systems. Stabilize environments to support audit readiness, SOX compliance, and regulatory requirements. Finance Stakeholder Partnership Serve as the primary technology partner to the CFO, Controller, FP&A, and Accounting teams. Translate complex technical constraints into business outcomes and align system roadmaps with Finance's strategic priorities. Team Leadership Build and lead a high-impact Finance Systems team. Foster a culture of curiosity, speed, and user-centricity — where the team is as proud of a clean reconciliation workflow as any external product shipped. What You'll Bring - 8+ years of experience leading finance systems or enterprise application functions in a fast-paced, high-growth environment - Deep, hands-on knowledge of ERP platforms (NetSuite strongly preferred) across core modules: GL, AP, AR, Fixed Assets, Revenue Recognition, Procure-to-Pay, Sales Audit, and International Consolidations - Strong understanding of Order-to-Cash and Procure-to-Pay process design, including the touchpoints between upstream sales/procurement systems and the ERP - Strong understanding of Sox IT General controls and track record implementing them - Proven track record designing and deploying AI/LLM-powered workflows or agentic systems to improve Finance team efficiency - Ability to design and govern scalable integrations and data flows across SaaS tools - Experience influencing Finance leadership, translating technical complexity into clear business decisions - Proficiency is an iPaaS platform (e.g., Workato, Mulesoft, Boomi, etc.) - Workato Certification is big plus - Proficiency in Python or SQL to personally prototype, audit, and quality-check automation logic - Familiarity with adjacent Finance tooling: expense management, FP&A platforms, billing systems, and treasury tools Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. The base salary range for this full-time position in the location of San Francisco is: $198,400 - $248,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Engineering Manager, AgentOps
At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About our AgentOps team: The vision for the AgentOps team is to build the best Agent Development Platform in the AI Industry. Agent Development is in its nascent stages in a rapidly changing industry, with limited tooling making it hard for agent developers to manage agent lifecycles. As a team that has a front-row seat to what Enterprise customers need and want, we want to build an opinionated but flexible platform for all Agent operations ("AgentOps"), including building, deploying, monitoring, evaluating and improving agents to solve customer needs. With the AI industry currently moving towards RL workflows that need verifiable rewards, we further want to gear this platform towards knowledge capture that create compounding effects to make Agents more effective and capable. We want to create a virtuous data flywheel where agents built using this platform see continuous performance improvements and increase customer value over time. We are a rapidly growing team with ambitious goals, and are looking for motivated individuals to join us to make an impact in a green-field domain. Responsibilities: - Manage the engineering team and drive technical delivery - Comfortable working cross functionally, whether that be internal or external customers - Work across the entire product lifecycle from conceptualization through production - Build features end-to-end: back-end, system design, debugging and testing - Deliver experiments at a high velocity and level of quality to engage our customers - Influence the culture, values, and processes of a growing engineering team - Inspire and mentor engineers - Collaborating with cross-functional teams to define, design, and ship new product features and experiences Requirements: - At least 5 years of relevant experience and at least 2 years of experience managing engineers is preferred - Proven success in leading, managing, and developing high-performing Engineering teams - Expertise in identifying product engagement patterns and trends for large scale consumer products - Track record of shipping high-quality products and features at scale - Desire to work in a very fast-paced environment - Ability to turn business and product ideas into engineering solutions - Excellent problem-solving skills, and be able to work independently or as part of a team. - Excited to join a dynamic, hybrid team in either San Francisco or New York City. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $252,000 - $315,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Engagement Management Lead
Scale's Generative AI business is continuing to see tremendous growth and expansion. As an Engagement Manager Lead, you will operate at the center of Scale's most strategic frontier AI lab customer relationships, serving as a trusted, operationally-grounded thought partner to the world's leading AI research teams. EM Leads build deep relationships with Gen AI researchers and other customer leads, navigate difficult conversations with confidence grounded in operational knowledge, and earn new work through driving exceptional customer success. EM Leads are naturally empathetic and excel at building long-term relationships through diligent problem solving and thoughtful, strategic discussions. You will: - Own a portfolio of complex, strategic accounts with full accountability for customer success and commercial development - Build and maintain deep, trust-based relationships with frontier AI lab researchers and operations leads, serving as a thought partner throughout the project lifecycle from ideation to execution - Navigate difficult customer conversations around quality, throughput and other delivery expectations with confidence and clarity grounded in deep operational knowledge - Identify and develop expansion opportunities through close customer engagement Ideally you'd have: - A technical background (education or professional experience with CS, Engineering, Economics, Statistics, or another STEM field) - 5+ years of in consulting or in a technical product or program management role - A proven track record in B2B client-facing roles, including building and expanding relationships and navigating complex customer dynamics - Ability to understand the ML training lifecycle and discuss use cases meaningfully with technical customers - Graduate degree (PhD, MS) or research experience in a STEM field - Experience at a frontier lab or company developing foundational models, or in a technical role at a high-growth AI company - Hands-on technical experience working with data or AI/ML models, whether through engineering, research, or a technical product role Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $192,800 - $241,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Deployment Engineering Manager, Enterprise
At Scale AI, our mission is to accelerate the development of AI applications. For 10 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About our Enterprise Team: Our team owns the full deployment lifecycle of SGP in live customer environments — from initial rollout through long-term operational health. We work cross-functionally with customers, GTM, product, and infrastructure to ensure every deployment is production-ready, secure, and built to last. We’re looking for an Infrastructure Engineering Manager to help shape the future of AI-powered applications. In this role, you’ll bridge the gap between AI research and production, leading a team that is turning innovative prototypes into scalable, high-performance enterprise solutions. Your team will work on interactive AI applications, enterprise SaaS products, and platform capabilities that redefine how businesses leverage AI. We don't just ship and move on. We stay close to the customer experience, translating real-world deployment challenges into platform improvements, automation, and scalable playbooks that make every future rollout smoother than the last. If you're energized by solving complex technical problems at the intersection of customer impact and platform excellence, this is the team for you. Responsibilities: - Define and execute the infrastructure roadmap aligned with business and engineering priorities. - Lead the design and implementation of scalable, secure, and reliable infrastructure systems. - Set and maintain SLAs/SLOs for platform uptime, performance, and developer experience. - Manage the engineering team and drive technical delivery - Design, build, and optimize backend services for advanced AI-driven applications, focusing on AI agents, evaluation tooling, and automation - Influence the culture, values, and processes of a growing engineering team - Inspire and mentor engineers. - Work closely with product, security, and engineering leadership to align on goals and priorities. Requirements: - At least 5 years of relevant experience and at least 2+ years of experience managing infrastructure or platform teams. - Proven experience with cloud platforms such as AWS, GCP, or Azure. - Deep understanding of CI/CD pipelines, infrastructure-as-code (e.g., Terraform, Pulumi), and container orchestration (e.g., Kubernetes). - Experience managing production environments with high availability, reliability, and scalability requirements. - Familiarity with monitoring, alerting, and incident response best practices. - Experience working with modern developer platforms and internal tooling to improve engineering velocity. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco and New York is: $216,000 - $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Member of Technical Staff (Software Engineer, Appl...
Perplexity is looking for an Applied AI Engineer to design, build, and iterate on cutting-edge agents powering our core experience in Perplexity Computer. Working in this mission critical team, you will develop frontier context layer applications - fulfilling the curiosity of millions of users across the globe. Key Responsibilities - Apply state-of-the-art ML and LLM techniques to solve problems spanning: - Personalization (LLM memory, context summarization, retrieval and ranking); - Contextual recommendations and Monetization applications - Build frontier agent capabilities on top of Perplexity Computer - Build auto research harness for both offline and online techniques, designing experiments and metrics that provide deep insight into quality and impact. - Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, and iterative improvement and build autonomous harness for agent squad to explore different problem spaces. - Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure our AI drives meaningful product improvements. - Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research and algorithms into the product lifecycle. Preferred Qualifications - 5+ years experience building and shipping robust AI products for large-scale, user-facing or data-driven products. - Strong software engineering skills (Python, production-quality codebases, collaborative development) and experience using agentic coding tools for large scale parallel developments. - In-depth experience with the full AI lifecycle: data analysis, rigorous evaluation, and ongoing monitoring/improvement. - Proven collaborator and communicator; excels in high-velocity, cross-functional teams. - Curious, driven by end-user/product impact, and passionate about advancing the state of applied ML and AI. - BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience). Bonus Points For - Experience with LLM context engineering or harness engineering. - Experience in mid-training or post-training frontier open source models - Experience in large scale user-centric and content-centric personalization challenges (user modeling, retrieval, content ranking, etc).
Member of Technical Staff (Data Scientist, Evals)
Perplexity serves tens of millions of users daily with reliable, high-quality answers grounded in an LLM-first search engine and our specialized data sources. We aim to use the latest models as they are released, but the intelligence frontier is a jagged one, and popular benchmarks do not effectively cover our use cases. In this role, you will build specialized evals to improve answer quality across Perplexity, covering search-based LLM answers and other scenarios popular with our users. RESPONSIBILITIES - Architect and maintain automated evaluation pipelines to assess answer quality across Perplexity's products, ensuring high standards for accuracy and helpfulness - Design evaluation sets and methods specifically to measure the impact of tool calls (particularly web search retrieval) on the final answer's quality - Develop VLM-based solutions to programmatically evaluate how final answers render visually across different platforms and devices - Continuously review public benchmarks and academic evaluations for their applicability to the Perplexity product, adapting and incorporating them into our regular performance measurements - Operate within a small, high-impact team where your evaluation metrics directly shape product changes, collaborating closely with technical leadership to measure and improve Answer Quality QUALIFICATIONS - PhD or MS in a technical field or equivalent experience - 4+ years of experience in data science or machine learning - Strong proficiency in Python and SQL (expected to write production-grade code) - Experience building within a modern cloud data stack, specifically AWS and Databricks - Comfortable with agentic coding workflows and using AI-assisted development tools to iterate faster PREFERRED QUALIFICATIONS - 1+ years of experience working with LLMs at scale, specifically with LLM-as-a-judge setups - Prior experience working on customer-facing web products or consumer apps, with real user traffic at scale - A strong research background, with experience applying research methods to real-world ML problems - Experience defining evaluation metrics (e.g., factual consistency, hallucination rate, retrieval precision) and building ground truth datasets
Member of Technical Staff (AI Inference Engineer)
We build and run the inference engine behind every Perplexity query and deploy dozens of model architectures at scale with tight latency and cost budgets. Our stack is Rust, Python, CUDA, and CuTe DSL - and we need another engineer to join us. WHAT YOU WILL WORK ON Examples of real work the team does: - New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway. - GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow. - Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic. - Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernel interleaving. - Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents. WHO WE'RE LOOKING FOR - Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus. - You understand modern LLM architectures and are able to bring them up reliably in a production environment. - You've built and operated production distributed systems under real load - ideally performance-critical ones. - Comfortable working across languages and layers: Rust for the serving runtime, Python for model code, CUDA/CuteDSL for kernels. - You own problems end-to-end. You can read a research paper on Monday, write a kernel on Wednesday, and debug a production incident on Friday. - Self-directed. You do well in fast-moving environments where the path forward isn't laid out for you. GOOD IF YOU TOUCHED ANY OF - ML compilers and framework internals: PyTorch internals, torch.compile, custom operators. - Distributed GPU communication: NCCL, NVLink, InfiniBand, RDMA libraries, model/tensor parallelism. - Low-precision inference: INT8/FP8/FP4 quantization, mixed-precision serving. - Profiling and debugging tools: Nsight Compute/Systems, CUDA-GDB, PTX/SASS analysis. - Container orchestration: Kubernetes, GPU scheduling, autoscaling inference workloads. QUALIFICATIONS - 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems. - Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow). - Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores). - Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation).
Engineering Manager (TLM, Agents)
Perplexity is seeking a TLM (Tech Lead Manager) to lead and grow our highly driven Agents engineering team. The Agents team consists of AI/ML, backend, and full-stack engineers who collaborate to build delightful agentic experiences within our Comet ecosystem https://www.perplexity.ai/comet. Our vision is to empower our users with AI agents that can faithfully actualize their intent, however and wherever expressed, through open-ended interactions with the world. As the Agents TLM, you will bring AI expertise, sharp product intuition, and strong engineering management skills to advance the frontier of what agents can accomplish for our millions of devoted users. You will lead, grow, and support a team in solving many open problems in AI, including: - Designing AI agents to navigate the digital world and perform increasingly valuable units of work for our users; - Training action and decision models that determine, based on complex multimodal states, how to accomplish user-specified objectives; - Providing consistently excellent experiences across desktop, mobile, headless cloud, and other environments through flexible abstractions and frictionless backgrounding; - Developing permission architectures, payload classifiers, and other methods to implement secure-by-design agentic capabilities; - Designing optimal data representations and modes of interaction between agents and their environments; - and much, much more. RESPONSIBILITIES - Provide technical leadership across multiple layers of a rapidly growing product in the AI agents space. - Develop and leverage cutting-edge AI models, infrastructure, and browser technologies to advance the capability frontier and scale those capabilities for a rapidly growing userbase. - Exercise sharp technical & product intuition to guide the team’s system architectures and product roadmaps. - Drive product reliability, code quality, AI evaluation, testing, and maintenance for the broader team. - Oversee hiring, onboarding, and mentorship for a rapidly growing team. Develop rigorous interview pipelines and work closely with recruiting to source candidates. - Interface with the Perplexity co-founders to deliver strategic objectives that redefine what’s possible in the AI industry. QUALIFICATIONS - Strong foundational familiarity with the full AI product stack. - Proficiency in Python (bonus points for TypeScript, Go, and/or Rust). - Domain expertise in at least one of the following areas: - Context engineering and tool interfaces for frontier AI models - Post-training and reinforcement learning (particularly for multimodal models) - Browser technologies (CDP, Playwright, extension development, etc.) - Strong product intuition and taste for user experience excellence. - Strong background and hands-on technical experience with frontier models (the more relevant to open-world agents, the better). - Strong organizational skills for managing and delivering parallel technical projects; ability to guide highly-opinionated teams in making sound tradeoffs and prioritization decisions is critical. - Experience managing engineering teams, including recruiting, growing, and retaining high-caliber talent. - 8+ years of engineering experience, with at least 3 of those years as an engineering manager.
Member of Technical Staff - ML Training Systems
ABOUT US: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable https://modal.com/blog/lovable-case-study, Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C https://modal.com/blog/modal-series-c at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for strong engineers with experience training production machine learning models. If you are interested in contributing to open-source projects and evolving Modal's infrastructure to train the next generation of language models, we'd love to hear from you! REQUIREMENTS: - 5+ years of experience writing high-quality, high-performance code. - Experience working with torch and high-level training frameworks (Huggingface, verl, slime) - Experience with ML training optimization (tell us a story about eliminating data loading bottlenecks, overlapping communications with compute, rewriting a trainer to handle off-policy rollouts, etc.) - Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc). - Ability to work in-person, in our NYC or San Francisco office. - Ability to participate in on-call rotation and respond to production incidents.
System Integrator Alliance Manager
ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. WHAT YOU'LL DO LangChain's platform is increasingly at the center of enterprise AI agent deployments — and a growing share of those deployments are built and delivered by system integrators (SIs). Your job is to make sure the SIs building on LangChain are set up to win: technically capable, commercially aligned, and positioned to grow their LangChain practices. This isn't a traditional channel role. The best SIs in this space move fast, operate closer to engineering teams than procurement, and care more about building real differentiation than logo badges. You'll need to meet them there. THE PROBLEMS YOU'LL BE SOLVING SIs are building AI practices right now — and they're making stack decisions that will compound over the next several years. LangChain has strong product and community traction, but converting that into structured SI partnerships requires someone who can: - Build relationships with the practitioners doing the actual work (architects, delivery leads, practice heads), not just executive sponsors - Help SI teams go deeper on LangChain technically — running enablement sessions, connecting them to the right internal resources, and making sure they can actually deliver - Create and close co-sell motions with SIs on active enterprise opportunities - Build joint go-to-market programs that make sense for how SIs actually run their business If you've sold or partnered through SIs before, you know the difference between a partnership on paper and one that drives real pipeline. We want someone who knows how to build the latter. WHAT YOU'LL OWN - Build and manage a portfolio of SI partnerships — from global SIs and consultancies to regional & boutique specialists - Run joint pipeline with SI partners: co-selling on active deals, running QBRs, tracking attribution - Design and deliver partner enablement: certifications, training, delivery playbooks, and technical workshops - Work with our solutions engineering and product teams to get partners unblocked on technical questions - Represent partner perspective internally — surfacing what SIs need in terms of product capabilities, support, and commercial terms - Develop co-marketing and thought leadership programs with key partners WHAT WE'RE LOOKING FOR Must-haves: - 5+ years in alliance management, partner sales, or business development — with direct experience working with SIs, GSIs, or consultancies - Genuine technical fluency in AI or developer tooling. You don't need to write production code, but you need to credibly discuss LLMs, agent architectures, and developer workflows - Track record of building SI partnerships, from the ground up, that drove measurable pipeline, not just signed agreements - Ability to manage relationships across multiple levels simultaneously — from engineers to practice heads to C-suite Nice-to-haves: - Experience at a developer tools or AI/ML infrastructure company - Existing relationships at major SIs or management consultancies with active AI practices - Familiarity with LangChain, LangGraph, or LangSmith — you've built with it, seen it deployed, or worked with teams using it LangChain is the open-source framework most teams reach for when they're building serious AI applications. We're a small team moving quickly, and this role has a real chance to shape how the SI ecosystem builds on top of what we're building. If that sounds like the right kind of problem, we'd like to talk. COMPENSATION AND BENEFITS - Annual salary range: $165,000 -$230,000 Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
Senior Fullstack Engineer, Growth & Monetization
ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Team The Growth & Monetization team focuses on how developers discover, adopt, and scale with LangChain’s products. We work across the full stack to improve onboarding, activation, and usage while building the systems that power billing, pricing, and monetization. This team partners closely with product, design, and go-to-market teams to understand developer behavior and translate those insights into product improvements that drive adoption and revenue. Our work directly shapes how developers and organizations move from experimentation to production on the LangChain platform. About the role LangChain is hiring a Senior Fullstack Engineer to build the foundational product features and integrations that power user acquisition, rapid experimentation, and self-serve expansion. This is a high-impact 0→1 role on a newly formed team responsible for building growth systems from the ground up. You’ll work closely with product, design, GTM, and analytics to streamline activation, optimize packaging, and deliver a seamless growth story for developers and enterprise customers alike. This role will be in person 5 days/week in New York City, San Francisco, or Boston. What you'll do - Work across our stack (React, TypeScript, Python, Go) to deliver full-stack product features that drive growth and retention - Build flexible experimentation systems and processes capable of targeting diverse growth metrics - Participate in data-driven, rapid growth experiments across the user funnel from onboarding to monetization - Design and ship new onboarding features and improvements that accelerate time to value - Build growth levers including usage-based guardrails, smart upgrade triggers, and contextual CTAs - Collaborate closely with product, design, GTM, and analytics teams to identify, prioritize, and execute high-impact growth opportunities What you'll bring - Extensive fullstack software development experience using React, TypeScript, and Go and/or Python - Strong product intuition and a track record of working on monetization, pricing, or activation features - Familiarity with usage metering, subscriptions, and internal tooling for pricing experiments - Comfortable working with REST APIs, Postgres, Redis, and modern backend infra - Startup DNA with the ability to thrive in fast-paced, zero-to-one environments - Self-directed with an ownership mindset - Bonus: Experience building for developers or product-led growth platforms - Bonus: Familiarity with LLMs, GenAI applications, or agentic frameworks Compensation - Salary Range: $175,000-$240,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
Product Marketing - LangSmith Fleet
ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE ROLE We’re looking for a Product Marketing Manager to help drive go-to-market for LangSmith Fleet, our product for bringing agents to every team in an organization. Fleet enables anyone to build, use, and manage agents with natural language — while giving organizations the security, observability, model flexibility, admin controls, and API extensibility they need to deploy agents responsibly across the business. It sits at the intersection of developer platform, enterprise SaaS, and end-user productivity. This role will help shape how we take Fleet to market across both sales-led and product-led growth motions. You’ll work on positioning and messaging, product launches, content, enablement, campaigns, customer storytelling, and cross-functional programs in partnership with product, sales, education, and marketing. The audience is broad and nuanced: technical buyers who care about security, observability, integrations, APIs, and governance; technical champions who want to extend and operationalize agents; and nontechnical users who need to understand what agents can do for their day-to-day work. You’ll help translate a rapidly evolving product into clear stories, content, and programs that drive awareness, adoption, and revenue. WHAT YOU’LL DO - Help launch new Fleet capabilities in a fast-moving market. You’ll partner with product and gtm to bring new features and use cases to market. - Develop positioning and messaging for Fleet. You’ll help define how Fleet shows up across the website, sales materials, launch assets, campaigns, product pages, and customer-facing content. - Create content that helps different audiences understand and adopt Fleet. This may include launch blogs, solution briefs, use case pages, customer stories, comparison pages, demo narratives, sales decks, guides, and campaign assets. - Build enablement for a sales-led motion. You’ll help equip sales and customer-facing teams with talk tracks, objection handling, discovery questions, demo narratives, competitive context, and materials that help them speak to technical buyers and business stakeholders. - Support PLG and adoption programs. Fleet is also a product businesses and users can try, build with, and adopt directly. You’ll help create onboarding, activation, lifecycle, and educational content that helps users understand what to build and how to get value. - Partner with demand generation on campaigns. You’ll help turn product narratives, use cases, launches, and customer insights into campaigns that drive pipeline and product adoption. - Stay close to customers and the market. You’ll synthesize customer conversations, sales feedback, product usage signals, competitive activity, and market trends into insights that improve our messaging, roadmap inputs, and GTM strategy. - Help define how Fleet fits into the broader LangSmith platform. You’ll connect the Fleet story to Observability, Evaluation, Deployment, Sandboxes, LangGraph, and the broader LangChain ecosystem. WHAT YOU’LL BRING - You have 2–4+ years of product marketing, developer marketing, or solutions marketing experience. - You’ve worked on technical products, developer tools, AI/ML products, B2B SaaS, infrastructure, automation, or platform products. - You can translate technical concepts into clear, customer-facing messaging. You don’t need to be an engineer, but you should be comfortable learning technical products and asking good questions. - You’re excited by a product that serves multiple audiences: developers, technical buyers, operators, admins, and nontechnical end users. - You understand how sales-led and product-led motions can work together. You can create materials that help sales teams win while also helping self-serve users understand and adopt the product. - You write clearly and quickly. You can turn a product capability, customer problem, or technical workflow into a compelling piece of content or enablement. - You like working cross-functionally. You’ll partner closely with product, sales, demand gen, devrel, education, customer-facing teams, and the broader marketing team. - You’re comfortable with ambiguity and iteration. Fleet is evolving quickly, and the market for workplace agents is still being defined. You’re excited to ship, learn, and improve. - You have genuine curiosity about agents and how they will change how teams work. - You use AI tools in your own work and are interested in finding new ways to increase your effectiveness with them. NICE TO HAVE - Experience marketing developer tools, AI products, automation products, productivity tools, or enterprise SaaS platforms. - Familiarity with the LLM, agent, or AI application development ecosystem. - Experience supporting both technical buyers and business/end-user audiences. - Experience partnering with sales on enterprise deals, including enablement, customer-facing storytelling, competitive support, or account-based campaigns. - Experience with PLG motions, onboarding, activation, lifecycle marketing, or self-serve adoption. WHY JOIN - You’ll help define a new category. Fleet is bringing agents from developer experiments into everyday work across companies. - You’ll work on a product with both end-user pull and enterprise depth. Fleet is easy to try, but also deeply connected to LangSmith’s security, observability, evaluation, deployment, and API capabilities. - Your work will directly shape how the market understands Fleet. This is a high-impact product area with room to influence messaging, launches, content, campaigns, and GTM strategy. - You’ll join a small, fast-moving team. You’ll get real scope, close access to product and GTM leaders, and the ability to ship meaningful work quickly. - Agents are where software is heading. LangChain is at the center of that shift, and you’ll help tell the story of how agents move from prototypes to real usage across companies. Compensation $125,000 to $165,000 + Equity Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
Customer Engineer (West Coast)
ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE ROLE We're looking for a Customer Engineer to join our Enterprise Enablement team. In this role, you will serve as a trusted technical advisor to our new customers, blending technical expertise with a passion for education and enablement. You will be instrumental in accelerating developer and enterprise success with the LangChain ecosystem. You'll join a collaborative team environment with a strong engineering culture, with direct impact on customer success and the opportunity to shape best practices while working with cutting-edge AI technology. ABOUT US: At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. WHAT YOU'LL DO - Lead onboarding engagements for new enterprise customers, guiding them through initial setup and unblocking issues as they begin building on the LangSmith platform - Create and deliver live, interactive training workshops to help customer teams build foundational product knowledge and agent engineering best practices - Develop scalable enablement frameworks including technical tutorials, best-practice guides, and reference implementations - Act as the voice of the new user, synthesizing feedback and identifying friction points to inform the product roadmap in collaboration with Product and Engineering teams - Partner with Sales, Deployed Engineering, and Professional Services to define enablement strategies for prospective customers, demonstrating the value and ease of getting started with LangChain - Stay at the forefront of agent engineering in industry to identify evolving trends and quickly incorporate learnings into customer enablement materials WHAT WE'RE LOOKING FOR - 5+ years of experience in a technical, customer-facing role such as Enablement, Customer Success Engineer, Developer Advocate, or similar - Proven software engineering experience with 2+ years focused on AI/ML applications or agents, including strong proficiency in Python and a deep, practical understanding of the modern AI/LLM stack - Passion for educating users on technical topics and deep empathy for the developer experience - Demonstrated ability to create and deliver high-quality technical training programs, including live workshops, written tutorials, documentation, and video guides - Exceptional presentation and communication skills, with the ability to explain complex technical concepts to diverse audiences, from individual developers to enterprise stakeholders - Capacity to operate independently in a fast-paced, ambiguous environment and manage multiple projects simultaneously - Ability and willingness to travel up to 20% of time for customer engagements Preferred: - Hands-on experience building and deploying applications using LangChain, LangGraph, and LangSmith (or similar frameworks) - Proficiency with TypeScript/JavaScript in addition to Python Compensation: - Base Salary $116,000-$195,000 Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
Software Engineer, Backend/Applied ML (Safety & In...
ABOUT THE ROLE We’re looking for a talented and creative Software Engineer to join our Safety Engineering team at Character.AI http://Character.AI! In this role, you will be at the forefront of designing, developing, and scaling robust backend systems and leveraging applied machine learning to tackle critical integrity and safety challenges. You will be architecting and implementing innovative solutions in a key role in addressing the unique safety challenges that come with human-to-AI interaction—bringing your technical expertise to the table as we define industry best practices in this emerging space. This is a high-impact role where you will provide technical leadership, drive innovation, and contribute to the core of our platform's trustworthiness. WHAT YOU'LL DO - Architect & Build: Design, develop, and maintain highly scalable, resilient, and performant backend systems that power our integrity and safety features. - Lead Complex Solutions: Lead the technical design and implementation of sophisticated backend solutions for detecting, preventing, and mitigating a wide array of integrity risks. This includes traditional issues (e.g., content classification, spam, etc.) as well as emerging threats related to Generative AI (e.g., misuse of generative models, generation of harmful or biased content, etc). - Apply Machine Learning: Conceptualize, develop, deploy, and iterate on machine learning models and algorithms to address complex integrity challenges. This includes areas like content classification (including AI-generated content), anomaly detection, risk scoring, behavior analysis, and developing safeguards for Generative AI systems (e.g., robust content filtering, bias mitigation techniques, and output monitoring). - Cross-Functional Collaboration: Work closely with product managers, data scientists, AI researchers, security teams, and operations to define requirements, design innovative solutions, and deliver impactful integrity systems, especially for Generative AI products. - Technical Strategy & Roadmap: Drive the long-term technical vision and roadmap for backend integrity systems and applied ML capabilities, with a keen eye on addressing Generative AI safety concerns with an alignment with company objectives. - Mentorship & Leadership: Provide technical guidance and mentorship to other engineers on the team and across the organization, fostering a culture of engineering excellence. - Champion Best Practices: Advocate for and implement best practices in software engineering, distributed systems design, data engineering, and the full lifecycle of ML model development, including specific considerations for the safety and ethics of Generative AI. - System Optimization: Continuously analyze and improve the performance, scalability, reliability, and cost-effectiveness of existing integrity platforms and ML models. - Stay Current: Keep abreast of emerging threats, new technologies, and advancements in backend engineering, distributed systems, the application of machine learning to trust and safety, and the evolving landscape of Generative AI safety research and mitigation techniques. WHO YOU ARE - 8+ years of professional software engineering experience, with a strong emphasis on backend systems development. - Bachelor's, Master's, or PhD degree in Computer Science, Engineering, or a related technical field. - Proven track record of designing, building, and operating complex, large-scale, and highly available distributed systems. - Expertise in one or more backend programming languages such as Python, Go, Java, or C++. - Hands-on experience in applying machine learning techniques to solve real-world problems, specifically with demonstrable experience in addressing integrity, trust, or safety challenges. - Solid understanding of the machine learning lifecycle, including data gathering and cleaning, feature engineering, model selection, training, validation, A/B testing, deployment, and operational monitoring. - Exceptional problem-solving abilities, with a knack for tackling ambiguous and technically challenging problems. - Proven ability to work in a fast-paced development environment and deliver timely results. - Strong communication, interpersonal, and leadership skills, with the ability to articulate complex technical concepts to diverse audiences. You will be a great fit if: - You care deeply about Trust & Safety and see it as a value-add to the business - Prior experience in a dedicated Trust & Safety, Integrity, or Risk engineering team. - Contributions to open-source projects or publications in relevant fields. - Experience leading large, cross-cutting technical projects. ABOUT CHARACTER.AI Character.AI http://Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI http://Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventures. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year—a testament to our innovative technology and visionary approach. Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI! At Character, we value diversity and welcome applicants from all backgrounds. As an equal opportunity employer, we firmly uphold a non-discrimination policy based on race, religion, national origin, gender, sexual orientation, age, veteran status, or disability. Your unique perspectives are vital to our success.
Software Engineer, Applied ML (Discovery, Recommen...
About the Role As a Software / ML Engineer you will work cross functionally with product, data science and data platform to identify, design and implement the applied ML models and infra, ranging from the model optimization, data pipeline to model training and serving infrastructure, on one of the fastest growing native AI consumer applications on the market today. You will work on implementation of our ML backend systems to power the discovery surfaces including recommendation, ranking and search, supporting new AI generated content formats on our product while working with the team to support optimizing our existing systems. Requirements: - B.A.S. in Computer Science or equivalent experience. - 5+ years of industry experience - Experience building/consuming RESTful and gRPC based web-services - Experience building and managing infrastructure in a cloud environment (GCP, AWS or Azure) - Familiar with one of the popular ML Frameworks like Pytorch, Tensorflow - Experience writing highly performant service in a modern typed language - Experience configuring and maintaining CI/CD pipelines and automated testing Desired Experience: - Experience with shipping intelligent features, end-to-end, and from idea to production - Experience with understanding, designing or implementing a full pipeline from data ingestion to model training. - Experience with production AI/ML systems and services including optimizing GPU/TPU deployments - Experience working with vector databases or other feature storage You will be a good fit if you are proactive and have a “get things done” mindset. Given our current pace of growth and load on our systems, most people have had a significant impact during their first week at the company. ABOUT CHARACTER.AI Character.AI http://Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI http://Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventures. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year—a testament to our innovative technology and visionary approach. Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI! At Character, we value diversity and welcome applicants from all backgrounds. As an equal opportunity employer, we firmly uphold a non-discrimination policy based on race, religion, national origin, gender, sexual orientation, age, veteran status, or disability. Your unique perspectives are vital to our success.
Research Engineer, Post-Training (All Industry Lev...
ABOUT THE ROLE AND TEAM Joining us as a Research Engineer on the Post-Training team, you'll be diving into the exciting world of fine-tuning AI models, optimizing their performance, and ensuring they meet the highest standards of quality and efficiency. Your work will directly contribute to our groundbreaking advancements in AI, helping shape an era where technology is not just a tool, but a companion in our daily lives. At Character.AI http://Character.AI, your talent, creativity, and expertise will not just be valued—they will be the catalyst for change in an AI-driven future. The Post-Training team is responsible for developing our powerful pretrained language models into intelligent, engaging, and aligned products. As a Post-Training Researcher, you will work across teams and our technical stack to improve our model performance and training methods, including data, compute and algorithms. You will get to shape the conversational experience of millions of users per day. WHAT YOU'LL DO - Develop alignment algorithms and loss functions to improve data sample efficiency. - Write data pipelines to process diverse web data into a format models can ingest. - Identify quality signals to understand our model’s performance in the real world. - Design sampling algorithms to improve serving efficiency of large generative models. WHO YOU ARE - "All Industry Levels": have at least PhD (or equivalent) - Write clear and clean production-facing and training code - Experience working with GPUs (training, serving, debugging) - Experience with data pipelines and data infrastructure - Strong understanding of modern machine learning techniques (reinforcement learning, transformers, etc) - Track-record of exceptional research or creative applied ML projects NICE TO HAVE - Experience with product experimentation and A/B testing - Experience training large models in a distributed setting - Familiarity with ML deployment and orchestration (Kubernetes, Docker, cloud) - Publications in relevant academic journals or conferences in the field of machine learning ABOUT CHARACTER.AI Character.AI http://Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI http://Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventures. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year—a testament to our innovative technology and visionary approach. Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI! At Character, we value diversity and welcome applicants from all backgrounds. As an equal opportunity employer, we firmly uphold a non-discrimination policy based on race, religion, national origin, gender, sexual orientation, age, veteran status, or disability. Your unique perspectives are vital to our success.
Research Engineer, Multimodal
ABOUT THE ROLE AND TEAM Joining us as a Research Engineer on the Multimodal team, you'll be at the forefront of building and advancing video and image generation models that bring AI characters to life in entirely new ways. Your work will directly shape how millions of users experience rich, expressive, and visually compelling AI interactions every day. The Multimodal team is responsible for training, fine-tuning, and deploying cutting-edge image, audio and video generation models that power Character.AI http://Character.AI's visual experiences. We work across the full model lifecycle — from data pipelines and training to deployment and product integration. As a Multimodal Research Engineer, you will own and advance our video model training efforts, including joint audio-visual generation and image-to-video. You will collaborate across research, product, and infrastructure to push the boundaries of what AI-generated visuals can look and feel like at scale. WHAT YOU'LL DO - Lead fine-tuning and continued training of video generation models, including image-to-video and joint audio-visual generation. - Design and experiment with novel model architectures for multimodal generation, including multimodal conditioning (voice, structured text, reference images). - Leverage techniques such as LoRA, RLHF, and full-parameter fine-tuning to improve model quality across diverse visual scenarios. - Design and build large-scale data pipelines and automated annotation workflows to support continuous model improvement. - Explore model compression, inference acceleration, and serving optimizations to enable efficient real-time video processing at scale. WHO YOU ARE - Strong passion for pushing the boundaries of visual AI, with a self-driven, hands-on approach to solving complex technical problems - Proficient in PyTorch with end-to-end experience across data processing, model training, and deployment - Solid understanding of video and image generation architectures, including diffusion models, DiT, ControlNet, and SOTA video generation models - Experience with multimodal model training, including working with audio, vision, and language modalities together - Experience with distributed training tools (FSDP, DeepSpeed, etc.) - Experience with large-scale data processing, dataset construction, and automated data cleaning NICE TO HAVE - Experience with joint audio-visual or speech-conditioned generation models - Experience with AIGC, video effects, character animation, or asset generation products - Familiarity with ML deployment and orchestration (Kubernetes, Slurm, Docker, cloud platforms) - Publications in relevant venues (NeurIPS, ICLR, CVPR, ECCV, ICCV, or similar) ABOUT CHARACTER.AI Character.AI http://Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI http://Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventures. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year—a testament to our innovative technology and visionary approach. Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI! At Character, we value diversity and welcome applicants from all backgrounds. As an equal opportunity employer, we firmly uphold a non-discrimination policy based on race, religion, national origin, gender, sexual orientation, age, veteran status, or disability. Your unique perspectives are vital to our success.
Staff+ Software Engineer, Backend
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: Anthropic is looking for experienced, product-minded engineers to own the backend systems that power user experiences across our API, Claude Code, and Claude.ai. You'll independently scope complex, multi-month projects through ambiguous problem spaces and lead peers through technical and product decisions; you'll drive alignment with product, peer engineering teams, and research to identify capability gaps and translate frontier model improvements into shipped products. You'll make architectural decisions that affect the reliability and scalability of systems serving hundreds of thousands of global users (including internal teams), and design processes that help your team operate effectively and never fail the same way twice - all while staying hands-on with the code and our models. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential: API Core : You'll build and scale the foundation of the Claude API—the systems that deliver Claude's intelligence to every developer, from startups to enterprise. You'll own the performance, reliability, and efficiency of our core serving path, ensuring users get the most speed and value from our models. You'll partner closely with inference and safeguards to optimize the full stack. API Capabilities: You'll bring frontier model capabilities to developers through the Claude API, owning core features like vision, tool use, and computer use. You'll launch new models and ship the primitives that make Claude more capable with every release. You'll partner directly with research and inference to productionize what's next. API Knowledge: You'll focus on transforming Claude into a true knowledge worker by ensuring the model has access to and understanding of the right knowledge at the right time. You'll work on making it possible for developers to securely give Claude access to their data while automatically processing and retrieving relevant information. You'll partner directly with research to bring state-of-the-art retrieval advancements to developers. Developer Experience: You’ll focus on building products and tools to enable developers to harness the full power of LLMs to create successful, reliable, and groundbreaking applications with ease. You’ll build the tools to accelerate developers from idea to deployment. You'll help figure out how to leverage Claude to improve developer's usage of the API, such as generating and evaluating prompts while collaborating closely with the teams above to bring Claude's current and future capabilities to developers. API Agents: You'll focus on building the infrastructure and APIs that enable developers to create powerful agentic applications within the Claude API. You'll help developers with agent orchestration through capabilities like tool use, multi-step reasoning, and long-running task execution that allow Claude to take actions and accomplish complex goals on behalf of users. You'll partner with research to bring cutting-edge agent capabilities to production. API Distributability: The Claude API today is a rapidly growing platform serving developers and enterprises at scale—but reaching the next tier of enterprise customers requires transforming how and where we deploy it. The Distributability team owns that transformation: making the Claude API a cloud-native, managed product that runs wherever our customers need it, cross-cloud and on Anthropic's own infrastructure, with the enterprise-grade security, compliance, and operational capabilities to support it. Enterprise Foundations: We're looking for a software engineer to join our Enterprise Foundations team—the team that makes Claude enterprise-ready at scale. When a Fortune 500 company wants to roll out Claude to 100,000 employees, we're the team that makes it possible.You'll build the foundational systems that large organizations require before they can deploy AI at scale: user and permissions management, security and compliance features, and analytics infrastructure. This work directly converts product-market fit into revenue by removing the deployment blockers that prevent large organizations from adopting Claude broadly. Passport: We're building the identity and verification product layer that enables safe model launches as Claude's capabilities expand. This critical effort partners with Safeguards, Auth & Identity, Policy, and Product teams across API, Claude.ai , and third-party platforms as customers, creating the systems for KYC/KYB, trust grant issuance and inheritance, and end-user verification that flow across every Anthropic surface. We sit at the intersection of trust, compliance, and product velocity, delivering the verification primitives that let Anthropic ship advanced model capabilities to the right users at massive scale. Marketplace: builds the platform that connects Claude-powered enterprise tools through technology partnerships and deeper customer relationships. We work closely with business development, sales, product, and GTM teams, creating the infrastructure that powers partner onboarding, customer storefronts, transaction and entitlement flows at scale. We're building the technical scaffolding for a new offering, tackling the challenges at the intersection of commercial motions, platform architecture, and partner integrations so that enterprises, platforms, and Anthropic can transact with confidence. You Might Be a Good Fit If You: - Have 8+ years of relevant experience as a backend or product engineer, with a track record of leading complex, multi-month projects or teams as a tech lead or equivalent - Have strong coding fundamentals and are comfortable working across backend systems, APIs, and integrations — and can reach into the frontend when needed to ship an effective solution - Have led the design and delivery of large-scale backend systems in production that power high-adoption B2B or consumer facing products - Are skilled at driving alignment across technical and non-technical teams; you communicate clearly, influence technical decisions beyond your immediate team, and help others ramp effectively on your systems - Take a product-focused approach to your work work and care about building solutions that are robust, scalable, and easy to use Care deeply about investing in the mentorship and growth of your peers - Have experience with distributed systems, API design, and cloud infrastructure at scale - Thrive in fast-paced environments and can navigate ambiguity to find the highest-leverage path forward The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 - $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Software Engineer, Safeguards Evals
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role How do we know our safety systems actually catch misuse? Anthropic increasingly uses AI to investigate potential misuse of Claude — analyzing real-world traffic to surface bad actors, policy violations, and emerging threats. Its findings inform enforcement actions and model launch decisions, which means we need rigorous, trustworthy answers to questions like: Does the monitoring agent catch what it should? Where does it fail? Does it stay reliable as adversaries adapt, as models improve, and as the agent itself changes? This role builds the evaluation infrastructure that answers those questions. You'll sit at the intersection of applied ML research and engineering — designing experiments to measure how well an investigative agent performs across harm areas, building datasets that represent real abuse rather than synthetic benchmarks, and shipping those methods into pipelines that gate every change to the system. Your work directly determines how much trust Anthropic can place in its automated abuse detection, and where we invest to make it better. Key responsibilities - Build and own the evaluation harness for an agentic investigation system — defining metrics, test cases and grading approaches for a complex long horizon agent - Construct high-quality eval datasets representing real-world misuse across harm areas (e.g., cyber attacks, bio weapons, influence operations), drawing from real traffic patterns and synthetic generation - Measure agent performance end-to-end (detection precision/recall, investigation quality, robustness) and drive hill-climbing on the hardest harm areas - Analyze coverage to identify measurement gaps, and evolve evals so they remain unsaturated and high-signal as agent capabilities advance - Productionize successful research into regression and release pipelines that run on every agent change, prompt update, and underlying model upgrade - Build tooling that enables policy experts to author, run, and iterate on evaluations without engineering support - Construct RL environments to improve Claude’s safety investigation capabilities. Minimum qualifications - Proficiency in Python and comfort working across the stack - Experience building and maintaining data pipelines - Experience working with LLMs and a working understanding of their capabilities and failure modes — especially agentic systems with tool use and multi-step reasoning - Strong data analysis skills — you can draw reliable insights from large datasets - Ability to move fluidly between research prototyping and production-quality code - Ability to translate ambiguous problems into concrete, testable experiments Preferred qualifications - 6+ years of industry software engineering experience - Expertise in building or contributing to agent evaluation frameworks, benchmarks, or automated grading systems - Extensive experience in trust and safety, content moderation, or abuse detection systems - Experience in red teaming, adversarial testing, or jailbreak research on AI systems - Experience with synthetic data generation or data augmentation - Experience with distributed systems or large-scale data processing - Experience with prompt engineering or building LLM-powered applications The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 - $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Senior Staff Software Engineer, API
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking an exceptional Senior Staff Software Engineer to join the Claude Developer Platform team and serve as the senior-most individual contributor across API Engineering. Since launch, the Claude API has seen rapid growth and adoption by companies of all sizes to build AI applications with our industry-leading models. The API serves as the primary channel for safely and broadly distributing AI's benefits across all sectors of the economy. This role sets the technical direction for the systems that make Claude accessible to developers, enterprises, and partners at scale. You will operate at the intersection of technical strategy and execution, partnering closely with Research, Inference, Platform, Infrastructure, and Safeguards to ensure the Claude API is reliable, capable, and positioned to grow with Anthropic's ambitions. This is a high-agency role that spans all API Engineering teams: API Core owns the foundational reliability and performance of the Claude API; API Capabilities ships frontier model capabilities—vision, tool use, computer use—directly to developers; API Knowledge builds retrieval and grounding systems that let Claude reason over external data; API Distributability ensures Claude reaches customers wherever they need it, with the enterprise-ready infrastructure to support it; and API Agents builds the infrastructure for long-horizon agentic workflows in production. Responsibilities - Define and drive multi-year technical strategy for the Claude API, setting direction across API Core, Capabilities, Knowledge, Distributability, and Agents. - Identify and personally lead the highest-complexity, highest-impact engineering initiatives spanning multiple teams. - Serve as the primary technical decision-maker for major architectural decisions with org-wide scope. - Partner with Research to evaluate and integrate frontier capabilities; work with Inference and Platform for reliable delivery at scale; collaborate with Infrastructure and Safeguards for reliability, security, and responsible deployment. - Mentor and develop Staff-level engineers across the org. - Drive alignment across Product, GTM, Safety, and beyond while proactively identifying and addressing systemic technical risks. You may be a good fit if you: - Have 12+ years of engineering experience with a clear track record operating at Staff or Senior Staff level. - Have demonstrably shaped technical strategy for large-scale API or distributed systems platforms. - Drive the highest-leverage technical outcomes without formal authority—you lead through influence, quality of thinking, and trust. - Have deep expertise in distributed systems and API architecture, and are effective writing design docs, making architectural calls, and coding in critical paths. - Are highly effective across org boundaries—you build trust with Research, Inference, Infrastructure, Safeguards, and business stakeholders alike. - Bring strong product instincts and a craftsperson's approach to API design; you communicate clearly with both technical and non-technical audiences. Technical Stack - Languages: Python, Golang, Rust - Infrastructure: GCP, AWS, Azure, Kubernetes - Databases: PostgreSQL (AlloyDB), Vector Stores, Firestore, Spanner - Tools: Feature Flagging, Prometheus, Grafana, Datadog, Claude Code Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in New York or the San Francisco Bay Area as these positions are part of an SF- or NY-based team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 - $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Research Scientist, Interpretability
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. We’re looking for researchers and engineers to join our efforts. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks using “microscopes” we build, or as treating neural networks as binary computer programs we're trying to "reverse engineer". A few places to learn more about our work and team at a high level are this introduction to Interpretability from our research lead, Chris Olah ; a discussion of our work on the Hard Fork podcast produced by the New York Times, and this blog post (and accompanying video) sharing more about some of the engineering challenges we’d had to solve to get these results. Some of our team's notable publications include A Mathematical Framework for Transformer Circuits , In-context Learning and Induction Heads , Toy Models of Superposition , Scaling Monosemanticity , and our Circuits’ Methods and Biology papers. This work builds on ideas from members' work prior to Anthropic such as the original circuits thread , Multimodal Neurons , Activation Atlases , and Building Blocks . We aim to create a solid foundation for mechanistically understanding neural networks and making them safe (see our vision post ). In the short term, we have focused on resolving the issue of "superposition" (see Toy Models of Superposition , Superposition, Memorization, and Double Descent , and our May 2023 update ), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent work found millions of features in Sonnet, one of our production language models, represents progress in this direction. In our most recent work, we develop methods that allow us to build circuits using features and use this circuits to understand the mechanisms associated with a model's computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks. We often collaborate with teams across Anthropic, such as Alignment Science and Societal Impacts to use our work to make Anthropic’s models safer. We also have an Interpretability Architectures project that involves collaborating with Pretraining. Responsibilities: - Develop methods for understanding LLMs by reverse engineering algorithms learned in their weights - Design and run robust experiments, both quickly in toy scenarios and at scale in large models - Create and analyze new interpretability features and circuits to better understand how models work. - Build infrastructure for running experiments and visualizing results - Work with colleagues to communicate results internally and publicly You may be a good fit if you: - Have a strong track record of scientific research (in any field), and have done some work on Interpretability - Enjoy team science – working collaboratively to make big discoveries - Are comfortable with messy experimental science. We're inventing the field as we work, and the first textbook is years away - You view research and engineering as two sides of the same coin. Every team member writes code, designs and runs experiments, and interprets results - You can clearly articulate and discuss the motivations behind your work, and teach us about what you've learned. You like writing up and communicating your results, even when they're null To learn more about the skills we look for and how to prepare for this role, see our blog post – So You Want to Work in Mechanistic Interpretability? Familiarity with Python is required for this role. Role Specific Location Policy: - This role is based in San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 - $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Research Engineer, Machine Learning (RL Velocity)
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you'll build and improve the core platform that underpins how we do RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster. This is high-leverage work: small improvements to velocity compound across every researcher and every run. Responsibilities - Build and improve the RL training infrastructure that researchers depend on day-to-day - Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed - Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster - Own the reliability and performance of research runs end-to-end - Contribute to design decisions that shape how Anthropic does RL at scale You may be a good fit if you - Have strong software engineering fundamentals and a track record of building performant, reliable systems - Have worked on ML infrastructure, distributed systems, or research tooling - Care about enabling other people's work and find leverage through platforms rather than individual experiments - Are comfortable operating across the stack, from low-level performance work to RL algorithms - Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego Strong candidates may also have - Experience with large-scale distributed training (RL, pre-training, or post-training) - Familiarity with JAX, PyTorch, or similar ML frameworks - A track record of operating at the edge of research and infra in a fast-moving environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £370,000 - £630,000 GBP Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Research Engineer, Cybersecurity RL (Reinforcement...
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Horizons The Horizons team leads Anthropic's reinforcement learning (RL) research and development, playing a critical role in advancing our AI systems. We've contributed to every Claude release, with significant impact on the autonomy, coding, and reasoning capabilities of Anthropic's models. About the role We're hiring for the Cybersecurity RL team within Horizons. As a Research Engineer, you'll help to safely advance the capabilities of our models in secure coding, vulnerability remediation, and other areas of defensive cybersecurity. This role blends research and engineering, requiring you to both develop novel approaches and realize them in code. Your work will include designing and implementing RL environments, conducting experiments and evaluations, delivering your work into production training runs, and collaborating with other researchers, engineers, and cybersecurity specialists across and outside Anthropic. The role requires domain expertise in cybersecurity paired with interest or experience in training safe AI models. For example, you might be a white hat hacker who's curious about how LLMs could augment or transform your work, a security engineer interested in how AI could help harden systems at scale, or a detection and response professional wondering how models could enhance defensive workflows. You may be a good fit if you: - Have experience in cybersecurity research. - Have experience with machine learning. - Have strong software engineering skills. - Can balance research exploration with engineering implementation. - Are passionate about AI's potential and committed to developing safe and beneficial systems. Strong candidates may also have: - Professional experience in security engineering, fuzzing, detection and response, or other applied defensive work. - Experience participating in or building CTF competitions and cyber ranges. - Academic research experience in cybersecurity. - Familiarity with RL techniques and environments. - Familiarity with LLM training methodologies. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 - $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Research Engineer / Scientist, Frontier Red Team (...
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team The Frontier Red Team (FRT) is a small, focused technical research team within Anthropic's Policy organization. Our goal is to make the entire world safer in an era of advanced AI by understanding what these systems can do and building the defenses that matter. In 2026, we're focused on researching and ensuring safety with self-improving, highly autonomous AI systems, especially ones related to cyberphysical capabilities. See our previous related work on exploits , partnering with Mozilla , and zero days . This is early-stage, high-conviction research with the potential for outsized impact — Glasswing is one example. Note: We are exclusively hiring in SF. We support relocation, but all hires must relocate before starting. About the Role In the last year, we've seen compelling signs that LLMs and agents are increasingly capable of novel cyber capabilities. We think 2026 will be the year where models reach expert-level, even superhuman, in several cybersecurity domains. This is a novel and massive threat surface. As a Research Scientist on FRT focusing on cyber, you'll build the tools and frameworks needed to defend the world against advanced AI-enabled cyber threats. Senior candidates will have the opportunity to shape and grow Anthropic's cyberdefense research program, working with Security, Safeguards, Policy, and other partner teams. This work sits at the intersection of AI capabilities research, cybersecurity, and policy—what we learn directly shapes how Anthropic and the world prepare for AI-enabled cyber threats. This is applied research with real-world stakes. Your work will inform decisions at the highest levels of the company, contribute to demonstrations that shape policy discourse, and build the technical defenses that we will need for a future of increasingly powerful AI systems. What You'll Do - Develop systems, tools, and frameworks for AI-empowered cybersecurity, such as autonomous vulnerability discovery and remediation, malware detection and management, network hardening, and pentesting - Design and run experiments to elicit and evaluate autonomous AI cyber capabilities in realistic scenarios - Design and build infrastructure for evaluating and enabling AI systems to operate in security environments - Translate technical findings into compelling demonstrations and artifacts that inform policymakers and the public - Collaborate with external experts in cybersecurity, national security, and AI safety to scope and validate research directions - Senior candidates will also set research strategy, define what problems are worth solving, own the technical roadmap, and manage relationships with cross-functional partners Sample Projects - Building frameworks and tools that enable AI models to autonomously find and patch vulnerabilities - Running purple-team simulations where AI defenders compete against AI attackers in network environments - Pointing autonomous AI systems at real-world security challenges (bug bounties, CTFs etc.) to characterize risks, defensive potential, and compare to human experts - Building demonstrations of frontier AI cyber capabilities for policy stakeholders You May Be a Good Fit If You - Have deep expertise in cybersecurity or security research - Are driven to find solutions to complex, high-stakes problems - Have experience doing technical research with LLM-based agents or autonomous systems - Have strong software engineering skills, particularly in Python - Can own entire problems end-to-end, including both technical and non-technical components - Design and run experiments quickly, iterating fast toward useful results - Thrive in collaborative environments - Care deeply about AI safety and want your work to have real-world impact on how humanity navigates advanced AI - Are comfortable working on sensitive projects that require discretion and integrity - Have proven ability to lead cross-functional security initiatives and navigate complex organizational dynamics Strong Candidates May Also Have - Experience with offensive security research, vulnerability research, or exploit development - Research or professional experience applying LLMs to security problems - Track record in competitive CTFs, bug bounties, or other security-related competitions - Experience building security tools or automation - Track record of building demos or prototypes that communicate complex technical ideas - Experience working with external stakeholders (policymakers, government, researchers) - Familiarity with AI safety research and threat modeling for advanced AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 - $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Research Economist, Economic Research
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As an Economist at Anthropic, you will work to measure and understand AI's effects on the global economy. You will make fundamental contributions to the development of the Anthropic Economic Index, establishing new methodologies to measure the usage, diffusion, and impact of AI throughout the economy using privacy-preserving tools and novel data sources. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions. Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system ( Clio ), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks. Responsibilities - Make fundamental contributions to the development and expansion of the Anthropic Economic Index , including quarterly reports and industry-specific deep dives - Design and conduct empirical research on AI's economic effects, drawing on external data sources and the privacy-preserving measurement systems internally - Develop new methodological approaches for studying AI's impact on: - Labor markets and the future of work - Productivity and task transformation - Economic inequality and displacement - Industry-specific disruption and adaptation - Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios - Develop causal-inference tooling — e.g. surrogate indexes, heterogeneous-effect pipelines — to help Anthropic evaluate the downstream economic consequences of its own compute, product, and pricing decisions - Build and maintain relationships with academic institutions, policy think tanks, and other research partners - Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection - Translate research insights into actionable recommendations for both product decisions and policy discussions - Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders You May Be a Good Fit If You Have - PhD in Economics - Strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning - Experience relevant to the study of AI’s impact on the economy, including: - Labor market analysis and occupational change - Task-based approaches to technological transformation - Large-scale data analysis and econometric methods - Large language models for social science research - Policy-relevant economic research - Experimental and quasi-experimental methods for causal inference - Macroeconomic modeling and time series forecasting - Agent-based modeling or large-scale simulation - Technical skills including: - Proficiency in Python, R, SQL, or similar tools for large-scale data analysis - Experience working with novel datasets and measurement systems - Comfort learning new technical tools and frameworks - Demonstrated ability to: - Lead complex research projects from conception to publication - Communicate technical findings to diverse audiences - Build relationships across academic, policy, and industry communities - Strong interest in ensuring AI development benefits humanity - Comfort working with AI systems and ability to think critically about their capabilities and limitations Some Examples of Our Recent Work - Anthropic Economic Index Report: Economic Primitives - Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption - Estimating AI productivity gains from Claude conversations - The Anthropic Economic Index Additional Information For this role, we're looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI's transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact. Application Question Please provide a writing sample, preferably a job-market paper or other article that showcases your research and technical expertise. Deadline to apply: None. Applications are reviewed on a rolling basis The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 - $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Product Manager, Compute Platform
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Product Manager focused on Compute Platform, you’ll partner with Infrastructure, Compute Operations, Engineering, Finance & Strategy, and Research to build the scheduling, orchestration, and capacity management systems that power Anthropic’s compute infrastructure—the foundation on which every model training run, evaluation, and inference workload depends: - Partner with Infrastructure to build the systems that determine how jobs are scheduled, prioritized, and allocated across Anthropic’s growing fleet of GPU and accelerator clusters—ensuring the right workloads run on the right hardware at the right time. - Your work directly impacts cluster utilization, cost efficiency, and researcher velocity: defining the semantic layer for job scheduling, establishing resource guarantees, and making the trade-offs that keep our infrastructure running at peak capacity. - You’ll drive the evolution of our compute platform to support increasingly diverse workloads—from large-scale training runs and fine-tuning jobs to real-time inference and batch evaluation—each with distinct scheduling requirements, priority levels, and resource profiles. - You will define and own the strategy and roadmap across job scheduling primitives, capacity allocation policies, preemption and fairness frameworks, quota management, and the observability tooling that gives engineering and leadership confidence in how compute resources are being used. Responsibilities: - Deeply understand the needs of internal customers across Research, Infrastructure, Product, and Finance—from researchers who need guaranteed resources for multi-week training runs to platform teams managing inference workloads with strict latency SLAs. - Define and iterate on the semantic layer for job scheduling: the abstractions, priority tiers, resource classes, and preemption policies that govern how work flows through our compute clusters. - Partnering with engineering leads to design scheduling capabilities that maximize cluster utilization while honoring resource guarantees—ensuring jobs have the right prerequisites (data, checkpoints, hardware affinity) validated before launch to avoid wasted compute. - Drive product strategy and roadmap for compute capacity management, including quota systems, fairness policies, bin-packing optimizations, and gang-scheduling for distributed workloads. - Own the trade-off framework between utilization efficiency, job latency, cost, and reliability—making transparent prioritization decisions and communicating them clearly to senior leadership. - Collaborate with the Capacity Strategy & Operations team on capacity planning models, demand forecasting, and cost-to-serve analytics that inform infrastructure investment decisions. - Build and champion observability tools and dashboards that provide real-time visibility into cluster health, queue depth, scheduling efficiency, and resource waste. You may be a good fit if you have: - 7+ years of product management experience, with deep exposure to compute infrastructure, distributed systems, or scheduling/orchestration platforms - Experience taking technical infrastructure products from infancy to scale—you’ve built something from the ground up and grown it to serve demanding internal or external customers - Track record of building platform products that balance the needs of multiple users and stakeholders—you’re comfortable making prioritization trade-offs between utilization, latency, cost, and fairness, and communicating them clearly - Ability to internalize complex technical systems (job schedulers, cluster managers, resource orchestrators) and translate that understanding into a comprehensive product vision - Fluent across functions—you’re equally credible discussing scheduling algorithms with engineers, capacity economics with finance, and infrastructure strategy with leadership - Strong instinct for connecting technical decisions to business outcomes: every percentage point of cluster utilization has measurable impact - Scrappy and resourceful—you do what it takes to get things done in a fast-moving environment Strong candidates may have: - Built or scaled job scheduling, resource orchestration, or workload management systems for large-scale compute clusters (e.g., Kubernetes, Slurm, Borg, YARN, or custom schedulers). - Deep familiarity with GPU/accelerator scheduling challenges, including gang-scheduling, topology-aware placement, preemption, and hardware affinity constraints. - Experience defining and enforcing SLAs and resource guarantees for compute workloads—including mechanisms to validate job prerequisites (data readiness, checkpoint availability, hardware compatibility) before scheduling to avoid wasted resources. - Capacity planning experience across cloud and on-premises infrastructure, including cost modeling, demand forecasting, and vendor management for compute procurement. - Scaled through hypergrowth in compute-intensive environments (AI/ML, HPC, large-scale cloud infrastructure). - Experience with observability and efficiency tooling for distributed infrastructure—building dashboards, automation, and governance workflows that drive utilization and cost accountability. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $305,000 - $385,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
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