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Machine Learning and Data Science Engineering Inte...
About the job Turn your machine learning coursework into insight that helps AI infrastructure run more reliably. As a Machine Learning and Data Science Engineer Intern, you will analyze telemetry from data center facilities and engineering infrastructure. You will apply data science and machine learning methods to real operational data. Your work will help engineers spot patterns, understand anomalies and make better-informed decisions. You will learn how infrastructure data connects to reliability, performance and day-to-day operations. You will clean and explore datasets, build reproducible analyses and evaluate predictive models. You will also create visualizations, document assumptions and share findings with technical colleagues. This internship gives you practical experience with real-world infrastructure data, supported by engineers who value curiosity and clear thinking. The team and culture You will work with the Facilities Reliability Engineering team in Austin. The team supports infrastructure used to develop and test the next generation of AI systems. Work happens through clear operational questions, shared data exploration, prototype analysis and practical review with engineers. Decisions are shaped by evidence, operational knowledge, reproducible results and honest discussion of uncertainty. You will own defined tasks with guidance, feedback and room to ask questions. As an intern, you will build confidence by turning data into insight engineers can use. What we’re looking for - Current enrollment at junior or senior undergraduate level, or in a master's program, in data science, AI, machine learning, computer science, statistics or a related field - Foundational knowledge of machine learning, statistics and data analysis through coursework, research, projects or practical experience - Programming experience in Python, with familiarity using common data-analysis libraries - Experience preparing, exploring, analyzing and visualizing datasets - Understanding of supervised machine learning concepts, including regression, classification, model training and model evaluation - Clear communication, a methodical approach to problem-solving and willingness to seek guidance when needed While we have outlined a set of requirements, we value transferable skills and diverse experiences. Benefits - Flexible working: Balance your work and personal life with greater flexibility - Comprehensive healthcare: Medical, dental and vision coverage to help keep you and your family healthy - Phantom equity: Share in Graphcore’s success - Tax-advantaged healthcare savings: Flexible Spending Accounts (FSAs) and Health Savings Accounts (HSAs) to help you make the most of your healthcare spending - Peace of mind protection: Disability and life insurance to provide financial security when you need it most - Retirement planning support: A 401(k) plan to help you invest in your future - Commuter benefits: Help cover the cost of your daily commute - Wellbeing resources: Access to wellness services that support your physical and mental health - Employee Assistance Program (EAP): Confidential advice and support for you and your family across a range of personal, financial and wellbeing matters We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work. We’re an equal opportunity employer and recognize that everyone brings different strengths and perspectives. If you need any accommodations during the interview process, just let us know - we're happy to support you. Join the Team at Graphcore Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore brings together deep expertise to solve complex problems and deliver meaningful progress in AI compute. Ready to spend your internship applying machine learning to real infrastructure data? Apply now to join Graphcore as a Machine Learning and Data Science Engineer Intern.
Software Engineer, Evals
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the Team Building a great AI assistant is only half the battle; knowing whether it is actually great is the other half. The Evals & Observability team owns the measurement and quality layer that makes Glean’s Assistant and Agents reliably better over time: evaluation pipelines, quality evalsets, LLM-powered judges, agent observability, and the tooling engineers use to understand what changed and why. This is a rare opportunity to work at the intersection of distributed systems, data infrastructure, applied AI, and product quality. You will help build the systems that decide whether new models, prompts, retrieval strategies, and agent workflows are ready to ship to enterprise customers. About the Role We are looking for backend and infrastructure engineers in Bangalore to build the platforms that measure, explain, and improve AI quality at scale. You will own core systems for running large-scale evaluations, processing traces, powering observability workflows, and giving engineers clear signals about assistant and agent behavior — including how Glean evaluates frontier model releases and the latest open-source model drops before they shape customer-facing AI experiences. This role is ideal for someone who loves building reliable distributed systems, cares deeply about product quality, and wants their infrastructure work to directly shape how AI products are shipped. You will work on systems that need to be scalable, secure, permissions-aware, fast, and cost-efficient. You will - Design and build large-scale evaluation pipelines that measure assistant and agent quality across thousands of real user and synthetic workflows. - Evaluate frontier model releases and the latest OSS model drops, building the infrastructure and quality signals that help Glean understand regressions, tradeoffs, and launch readiness. - Build agent observability infrastructure, including trace enrichment, durable telemetry pipelines, dashboards, and debugging workflows that make AI behavior inspectable. - Own backend systems from architecture and design docs through production rollout, reliability, monitoring, and iteration. - Partner with product, ML, and infrastructure engineers to make evals a first-class part of how Glean ships AI features. - Improve the quality loop by connecting eval results, customer feedback, regression analysis, and engineering workflows into concrete product improvements. - Build systems that balance speed, reliability, enterprise security, and cost across modern cloud-native environments. - Mentor other engineers, raise the bar for technical design, and help shape the engineering culture of Glean’s Bangalore AI quality team. About you - You have 6+ years of software engineering experience building backend systems, infrastructure, distributed systems, or data platforms. - You have strong coding skills in Go, Python, Java, C++, or similar languages, with an emphasis on reliability, scale, and well-tested components. - You are comfortable working with distributed data pipelines, production services, observability systems, or cloud-native infrastructure. - You are analytically rigorous and care about whether metrics reflect real user experience, not just whether dashboards look good. - You enjoy customer-focused, cross-functional environments and are willing to take on whatever is most impactful for the company. - You care deeply about quality, both in the systems you build and in the AI product you help measure and improve. - Experience with LLM applications, evals, tracing, data warehouses, workflow orchestration, or ML infrastructure is a strong plus. Location: - This role is in person in Bangalore, India Compensation & Benefits: Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy . By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement . By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.
Senior Data Scientist, Growth
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the Role: Glean is building a world-class data organization spanning data science, applied science, data engineering, and business analytics. This role sits within the Growth and Enterprise Readiness Data Science team, with a primary focus on accelerating user adoption, engagement, and sustained product usage. As a Growth Data Scientist, you will be the quantitative partner to Growth Product, Engineering, and Applied AI (Post Sales). You’ll turn ambiguous growth opportunities into measurable product bets, build the measurement and experimentation systems that allow us to learn quickly, and use behavioral data to identify where Glean can create substantially more value for its users. You will: - Define and evolve Glean’s growth measurement framework across acquisition, activation, engagement, retention, resurrection, and expansion, including metrics such as WAU, activation, engagement intensity, retention, and feature adoption - Build and analyze end-to-end user and account growth funnels to understand where users experience value, where they drop off, and which behaviors are most predictive of durable engagement - Diagnose adoption gaps and develop bottoms-up growth strategies for high-impact enterprise accounts, identifying where product, deployment, engagement, or organizational barriers are limiting growth and partnering with Applied AI and R&D leaders on targeted interventions. - Identify and size high-leverage growth opportunities across onboarding, product discoverability, education, lifecycle messaging, collaboration and virality, and new product surfaces - Partner across R&D and Applied AI to turn product capabilities and behavioral insights into scalable adoption plays, identifying the customers and user populations best suited for new experiences and translating those opportunities into targeted field interventions. - Partner closely with Product, Design, and Engineering to translate product ideas into testable hypotheses, well-defined success metrics, instrumentation plans, and decision criteria - Design and analyze rigorous A/B tests, phased rollouts, and quasi-experiments; use causal evidence to recommend whether products should launch, iterate, or change direction - Develop behavioral and needs-based user segments and translate those insights into targeted product interventions - Inform roadmap and investment decisions by quantifying reachable populations, expected impact, confidence, dependencies, and tradeoffs before significant development begins - Build trusted, reusable growth datasets, dashboards, and self-serve analytical tools that allow Product and Engineering partners to independently understand product health and investigate changes - Lead cross-functional data science projects end-to-end, translating ambiguous product questions into clear insights, recommendations, and decisions for audiences ranging from engineers to executives Example areas of focus could include improving new-user onboarding and activation, converting occasional users into habitual users, increasing adoption of emerging AI experiences, optimizing high-traffic entry surfaces, improving feature discovery, developing lifecycle strategies, and building account-level adoption frameworks for enterprise customers, and translating new product capabilities into scalable Applied AI adoption motions. You are: - 7+ years of experience in a highly quantitative data science, product analytics, or growth analytics role, with a degree in Statistics, Mathematics, Computer Science, or a related field - Demonstrated experience partnering with Product and Engineering teams to identify opportunities and influence product roadmap decisions - Strong grounding in statistics, experimentation, causal inference, statistical power, segmentation, funnel analysis, and retention analysis - Exceptionally high AI proficiency through habitual, high-value use of LLMs, with sound judgment about when and how to apply them, rigorous validation, and continuous workflow improvement - Experience designing and analyzing product experiments and communicating causal findings in a way that drives clear product decisions - Strong proficiency in SQL and practical fluency in a statistical programming language such as Python or R - Experience building durable analytical datasets, metrics, dashboards, and data models rather than relying primarily on ad hoc analysis. dbt experience is a plus. - A strong product and business mindset, with experience defining KPIs, guardrail metrics, and measurement frameworks that influence decisions - Ability to independently own complex projects end-to-end, from problem framing and measurement through analysis, recommendation, and follow-through - Clear, concise communication skills, with the ability to explain complex quantitative findings to both technical and non-technical audiences You are a particularly good fit if: - You have experience in B2B SaaS, especially enterprise AI, or have worked on products where adoption occurs across both users and accounts - You have experience partnering with GTM or Post-Sales teams and are comfortable using data to challenge assumptions, shape account strategy, and drive impact through action. - You have a track record of identifying growth opportunities from behavioral data and turning them into shipped, measurable product interventions - You have helped build experimentation or product-measurement capabilities that increased the velocity and quality of decision-making for an organization - You combine strong quantitative rigor with product intuition and are comfortable making recommendations in highly ambiguous problem spaces - You have a very strong sense of ownership and self-motivation. You are laser-focused on delivering business impact while growing as an individual along with Glean - You are good at managing evolving priorities while successfully delivering core initiatives Location: - This role is hybrid (4 days a week in our Mountain View office) Compensation & Benefits: The standard base salary range for this position is $200,000 - $260,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. We’re committed to building and sustaining a diverse, inclusive workplace. We strive to attract and retain people with a wide range of backgrounds, experiences, and perspectives, and we do not discriminate on the basis of gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. LI-HYBRID AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy . By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement . By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.
AI Success Manager, West
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the Role As an AI Success Manager, you will be a trusted advisor and strategic partner to a portfolio of Glean’s strategic and enterprise customers. You will work directly with executives, business leaders, technical teams, and practitioners to understand their goals, workflows, personas, and challenges. You will help customers imagine what is possible with Glean and rethink how work can be done across their organizations. This includes uncovering opportunities they have not yet identified, shaping new AI-powered ways of working, and turning those ideas into practical use cases and adoption plans. You will own the full customer journey - from understanding the business and defining the opportunity, through use-case design, deployment readiness, end-to-end deployment, change management, adoption, measurement, and expansion. You will be accountable for helping customers move from ideas to production and from production to measurable business results. You will own the overall customer plan and outcomes, while partnering with AI Outcomes Managers on function-level enablement, prompting, agent building, and user adoption. In This Role, You Will - Build trusted relationships with executives, business leaders, technical teams, and practitioners; understand their goals, workflows, personas, and challenges. - Help customers imagine what is possible with Glean and identify new ways AI can improve how people and teams work. - Discover and prioritize high-impact use cases, then turn them into clear roadmaps with owners, milestones, and success measures. - Own deployment readiness and lead end-to-end deployment, from technical planning and configuration through rollout, go-live, and production support. - Drive adoption and organizational change with AI Outcomes Managers, including training, champions, prompting, agent building, and enablement. - Define value hypotheses, baselines, KPIs, and ROI measures; lead post-deployment reviews to assess results and determine next steps. - Maintain a clear view of customer readiness, technical health, adoption, value, risks, and opportunities; lead Executive Business Reviews around these areas. - Monitor usage and adoption to improve how customers use Glean and expand successful use cases across teams and workflows. - Share customer patterns and unmet needs with Product, R&D, and company leadership while prioritizing the work most likely to drive customer results. You May Be a Good Fit If You Have - 6+ years in enterprise AI or technology transformation roles, including Customer Success, Technical Account Management, AI consulting or deployment, Solutions Consulting, Solutions Architecture, Strategy Consulting or Value Consulting. - Experience advising executives and business leaders at large or complex companies. - The ability to understand how businesses and teams work, identify where AI can help, and turn those opportunities into practical plans. - A track record of helping customers move from an undefined opportunity to a use case, deployment, adoption, and measurable results. - Experience leading change-management programs and measuring the value of technology investments. - Strong technical ability, including familiarity with APIs, SDKs, integrations, permissions, data flows, security, and enterprise deployment issues. - Strong consulting and communication skills, including discovery, workflow mapping, problem framing, use-case prioritization, and executive communication. - The ability to work credibly with executives, technical teams, and end users while managing multiple priorities. - Genuine curiosity about how businesses operate and how AI can help people work better. Location: - This role is hybrid (4 days a week in our San Francisco or Mountain View office) Compensation & Benefits: The standard OTE range for this position is $140,000-$200,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. LI-HYBRID AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy . By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement . By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.
AI Success Manager, Central
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the Applied AI Team The Applied AI team works with Glean’s strategic customers to turn AI capabilities into meaningful business results. We help customers understand where AI can have the greatest impact, imagine new ways of working, identify and launch high-value use cases, help employees adopt them, and measure the results. We work closely with customer executives and practitioners, Product, Engineering and Sales. What we learn from customers helps shape Glean’s products, adoption programs, and broader AI strategy. About the Role As an AI Success Manager, you will be a trusted advisor and strategic partner to a portfolio of Glean’s strategic and enterprise customers. You will work directly with executives, business leaders, technical teams, and practitioners to understand their goals, workflows, personas, and challenges. You will help customers imagine what is possible with Glean and rethink how work can be done across their organizations. This includes uncovering opportunities they have not yet identified, shaping new AI-powered ways of working, and turning those ideas into practical use cases and adoption plans. You will own the full customer journey - from understanding the business and defining the opportunity, through use-case design, deployment readiness, end-to-end deployment, change management, adoption, measurement, and expansion. You will be accountable for helping customers move from ideas to production and from production to measurable business results. You will own the overall customer plan and outcomes, while partnering with AI Outcomes Managers on function-level enablement, prompting, agent building, and user adoption. In This Role, You Will - Build trusted relationships with executives, business leaders, technical teams, and practitioners; understand their goals, workflows, personas, and challenges. - Help customers imagine what is possible with Glean and identify new ways AI can improve how people and teams work. - Discover and prioritize high-impact use cases, then turn them into clear roadmaps with owners, milestones, and success measures. - Own deployment readiness and lead end-to-end deployment, from technical planning and configuration through rollout, go-live, and production support. - Drive adoption and organizational change with AI Outcomes Managers, including training, champions, prompting, agent building, and enablement. - Define value hypotheses, baselines, KPIs, and ROI measures; lead post-deployment reviews to assess results and determine next steps. - Maintain a clear view of customer readiness, technical health, adoption, value, risks, and opportunities; lead Executive Business Reviews around these areas. - Monitor usage and adoption to improve how customers use Glean and expand successful use cases across teams and workflows. - Share customer patterns and unmet needs with Product, R&D, and company leadership while prioritizing the work most likely to drive customer results. You May Be a Good Fit If You Have - 6+ years in enterprise AI or technology transformation roles, including Customer Success, Technical Account Management, AI consulting or deployment, Solutions Consulting, Solutions Architecture, Strategy Consulting or Value Consulting. - Experience advising executives and business leaders at large or complex companies. - The ability to understand how businesses and teams work, identify where AI can help, and turn those opportunities into practical plans. - A track record of helping customers move from an undefined opportunity to a use case, deployment, adoption, and measurable results. - Experience leading change-management programs and measuring the value of technology investments. - Strong technical ability, including familiarity with APIs, SDKs, integrations, permissions, data flows, security, and enterprise deployment issues. - Strong consulting and communication skills, including discovery, workflow mapping, problem framing, use-case prioritization, and executive communication. - The ability to work credibly with executives, technical teams, and end users while managing multiple priorities. - Genuine curiosity about how businesses operate and how AI can help people work better. Location: - This role is remote (must be located in US Central timezone) Compensation & Benefits: The standard OTE range for this position is $120,000-$170,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. LI-REMOTE AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy . By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement . By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.
Foundation Models
What You'll Do - Build machine learning models for robotics control end-to-end: data curation, careful evaluation, model architecture, training/inference stacks, rigorous experiments - Collaborate with simulation and real-world robotics teams to curate high-quality, diverse, and large-scale datasets - Curate the world’s best Internet-scale datasets for embodied perception and first-person robot video generation - Design new generative simulation techniques to expand simulation data scale and diversity, training and evaluating generative models of 3D objects and environments, and language/code models to generate tasks and reward functions - Collaborate with a team of driven individuals committed to building general-purpose Physical AI What You'll Bring - Passion for your craft and demonstrated excellence in full-stack foundation model research and engineering - Exceptional ownership and initiative—finding and solving problems independently - Extensive experience pioneering new machine learning ideas or refining existing methods, supported by first-author publications or impactful projects (5+ years) - A relentless commitment to data and code quality, rigorous evaluation, and meticulous attention to detail - Production-level expertise in modern Python - Bonus: Experience with Vision-Language-Action models for robotics or web agents, embodied perception, or video generation
Software Engineer: ML Robotics Systems
ABOUT GENERALIST At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done. We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world. The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, https://research.google/blog/palm-e-an-embodied-multimodal-language-model/ RT-2 https://deepmind.google/blog/rt-2-new-model-translates-vision-and-language-into-action/, Gemini Robotics https://deepmind.google/models/gemini-robotics/), launched and scaled ChatGPT https://chatgpt.com/ and GPT-4 https://openai.com/index/gpt-4-research/ to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas https://bostondynamics.com/atlas/, Spot https://bostondynamics.com/products/spot/, Stretch https://bostondynamics.com/products/stretch/) and pushed the limits of what they can do (from parkour https://www.youtube.com/watch?v=tF4DML7FIWk to manipulation https://bostondynamics.com/blog/large-behavior-models-atlas-find-new-footing/, and testing robustness https://www.youtube.com/watch?v=aFuA50H9uek). We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. ABOUT THE ROLE You will tackle end to end problems that make our AI models work better on robots. You might add new functionality to our video processing data pipeline, then update our ML data loader, then train some models to validate your change, then test those changes in the real world on a robot. This requires stringing together many distributed python services to accomplish a given data processing, or application processing task. It also requires marshaling large quantities of cloud infrastructure to process this business logic efficiently at scale. You’ll be responsible for: - Designing and implementing any new idea that can help make our entire system more robust, scalable, or faster - Overhauling existing systems and services to handle the next 10x of scale - Writing the business logic that gets our robot the data it needs, or the business logic that gives our customers the right access to our robots. You might thrive in this role if you: - Have extensive experience building complex distributed applications or data pipelines at scale - Have experience processing petabytes of data (bonus if it’s video data) - Expertise in python, basic distributed infrastructure skills, and solid modern ML fundamentals - Have a solid foundation in modern ML techniques and experienced large scale ML training and production deployments - Have experience with distributed cloud infrastructure and a solid understanding of cloud networking, permissions, and container orchestration (Kubernetes).
AI Engineer
ABOUT THE ROLE You'll own the core AI systems that power Gamma: the models, prompts, and pipelines behind text, image, and layout generation. With over 1 million AI-generated presentations and 6 million AI images created every day, this work operates at massive scale. Your job is to elevate quality, evaluate new frontier models, and push into new capabilities and modalities. This role is about productizing existing foundation models, not training new ones. You'll focus on prompting, evaluating, and fine-tuning for maximum performance across Gamma's product surface. You'll also launch new modalities like voice and video, build the evaluation infrastructure to measure what "good" looks like, and own uptime, latency, and cost across our AI stack. You'll work closely with engineering and product to ship improvements that millions of users feel immediately. You'll thrive here if you're a tinkerer who loves pushing foundation models to their limits and you're equally comfortable writing prompts and writing production code. If you get excited about mixing prompt engineering with software engineering to unlock new AI capabilities, this is your role. Our team has a strong in-office culture and works in person 4–5 days per week in San Francisco. We love working together to stay creative and connected, with flexibility to work from home when focus matters most. WHAT YOU'LL DO - Own Gamma's LLM and image prompts, measuring and continuously improving quality at scale across text, layout, and visual generation - Develop complex prompts for new features using AI JSX, balancing creativity with reliability - Build evaluation frameworks for prompts and models, combining quantitative metrics with qualitative feedback to create better test sets - Drive the AI roadmap based on quality gaps, constantly evaluating new frontier models and methods - Curate datasets for fine-tuning open-source models and launch new modalities like voice and video - Own analytics, tracking, uptime, latency, and cost across Gamma's AI infrastructure WHAT YOU'LL BRING - Proven track record pushing foundation models to their limits, with hands-on experience building and evaluating prompts at scale - Proficiency in TypeScript and Python, with a software engineering foundation that lets you move fluidly between prompt engineering and production development - Strong data instincts: experience writing evals, designing metrics, and translating qualitative feedback into measurable, actionable improvements - Self-sufficient in gathering and cleaning data to inform prompt improvements and model evaluations - Experience with modern LLMs and image models such as Flux and Imagen (Nice to have) - Familiarity with AI tooling like AI JSX for prompting and Braintrust for evaluations (Nice to have) COMPENSATION RANGE: The base salary for this full-time position, which spans multiple internal levels depending on qualifications, ranges between $180K - $300K plus benefits & equity. Final offer amounts are determined by multiple factors, including but not limited to experience and expertise in the requirements listed above. If you're interested in this role but you don't meet every requirement, we encourage you to apply anyway! We're always excited about meeting great people.
Software Engineer, AI Application
About FuriosaAI FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa operates globally with offices in Korea and Silicon Valley, along with a compiler-focused R&D lab in Lisbon. Our vision is to make AI computing sustainable, enabling access to powerful AI for everyone on Earth. We solve the AI hardware energy and operational cost crisis at the architectural level, rather than through brute force, building the world's first truly AI-native compute platform to unlock the full potential of artificial intelligence for every enterprise. About the Role Develop a comprehensive AI reference application and maintain internal AI services to accelerate real-world deployment of RNGDs. Key Responsibilities Develop high-impact AI applications and technical resources to enable the success of the global developer community. - Develop enterprise-focused, high-quality reference applications and sample code that enable developers to effectively understand and utilize FuriosaAI’s SW stack and integrations. - Drive end-to-end application enablement such as RAG systems, agentic systems, and RL inference engines on FuriosaAI accelerators, creating reproducible guides and reference implementations. - Evaluate applications against real-world scenarios to validate performance, reliability, and usability of RNGD deployments. - Support live application demos and collaborate with the global developer community through GitHub and open-source channels to improve real-world usability. Minimum Qualifications - BS in Artificial Intelligence, Computer Science, Electrical Engineering, or a related field. - Experience in full-stack (frontend and backend) development of AI services. - Experience collaborating across engineering, product, and design teams to align software development with product requirements. Preferred Qualifications - MS or PhD in Artificial Intelligence, Computer Science, Electrical Engineering, or a related field. - Experience in developing and maintaining AI products, including running A/B tests and operating services under high traffic. - Experience in open-source projects on AI applications such as agentic systems, RAG, or multimodal pipelines. Why Join FuriosaAI The defining bottleneck of the AI era is building the right hardware and software stack to run it at global scale. Furiosa is solving this challenge holistically from the ground up. With our flagship chip, RNGD, in mass production today and our next-generation platform in development with Broadcom, we are proving that full-stack, tensor-native compute is the future of AI infrastructure. This is a pivotal moment to join our team, right as we accelerate our global expansion. At Furiosa, you will: Solve AI’s Most Urgent Challenge. Help build the high-performance, energy-efficient inference hardware and software required to fulfill the promise of advanced AI. Pioneer Full-Stack Co-Design. Work with teams that are architecting solutions from silicon up through the compiler (featuring innovations like Tensor Contraction Language and Virtual ISA) and serving frameworks. Ship Real-World Silicon, Software, and Solutions. Turn breakthrough technology into commercial deployment. RNGD is in mass production with TSMC and running live enterprise workloads for global leaders like LG AI Research and Samsung SDS. Partner With the Industry's Best. Collaborate across an elite global ecosystem that includes TSMC, Broadcom, SK Hynix, and GUC. Do Your Life’s Best Work. Join a brilliant, low-ego, mission-driven team in a high-trust environment that values autonomy, intellectual curiosity, and shared ambition. Contact - recruit@furiosa.ai
Software Engineer, Applied AI
ABOUT FLUIDSTACK We exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had to do. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it. We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI. We hire people who care deeply about this problem space. If that is you, please apply! HOW WE OPERATE - Be a barrel. Full autonomy. Own things end to end, take on scope without being asked, no permission required to operate outside your core role. - Insane urgency. We drive everything forward as fast as possible. - Reason from first principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins. - Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward. - Build something that actually matters. If you're going to spend your time, spend it on something that matters to the world. HOW WE OPERATE - Extreme ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done. - Velocity. We drive everything forward as fast as possible. - First principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins. - Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward. THE SOFTWARE ENGINEERING TEAM EXAMPLES OF KEY EXCITING PROBLEMS THE TEAM IS WORKING ON: - We're building the pipeline that processes thousand-page vendor unstructured material against our own DC design to automate the generation of an end to end site design and schedule. - We're building the live model of a AI infrastructure project’s entire delivery schedule, durable workflows handing off across every team, to replace static Gantt charts with a plan that updates itself as reality changes. - We're building the agent platform that wraps AI in real authorization, audit, and guardrails, to let agents accelerate the development of infrastructure instead of just advising report on it. ROLE SCOPE - Build core primitives end to end. Entity ownership, audit, authorization, orchestration. You make the right thing the default and the wrong thing hard. - Own the domain model. Turn Fluidstack's world of power, datacenters, and chips into composable entities that still hold up years from now. - Define interactions with the outside. Interface with vendor systems and ingest the formats our domain actually speaks: KMZ, BIM, Revit, vendor docs. - Make AI agents first-class operators of our systems. Give them the tools, guardrails, and audit trails to act safely, not just advise. WHAT WE'RE LOOKING FOR The below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly, tell us where you would. https://jobs.ashbyhq.com/fluidstack/05c2e69c-42f9-4fcb-9cf0-a467aaf98f1c - You move toward ambiguity, not away from it. You walk into the fog, build the map, and explain it to everyone else. - You learn at a steep slope. You reach real competence in an unfamiliar domain fast, whether it's a workflow engine, an authz model, or a geospatial format. We value this over existing expertise. - You have taste in abstraction. You see the one primitive hiding under five janky one-offs, and you know when not to abstract. - You model domains with rigor earned the hard way. You've gotten it wrong, felt the pain, and never forgot it. - You pull structure out of mess. You've done real work turning messy, unstructured data into something usable, in ML, data engineering, or research. - You're fluent with AI tooling. LLM APIs, MCP servers, and agentic frameworks, and you drive Claude Code, Cursor, or similar every day. - You've shipped production code that other people depend on, and you're comfortable in any language using AI coding tools. - Bonus: MLE work, especially extraction and synthesis from unstructured data. Workflow and orchestration engines (Temporal, Cadence, Airflow). Geospatial (KMZ/GIS) or BIM (Revit, IFC). Authorization and policy engines (OPA, Zanzibar-style, RBAC/ABAC). Audit or event-sourcing systems. Go, TypeScript, and Postgres. SALARY & BENEFITS - Competitive total compensation package (salary + equity). - Retirement or pension plan, in line with local norms. - Health, dental, and vision insurance. - Generous PTO policy, in line with local norms. Total compensation may also include equity in the form of restricted stock units. We are committed to pay equity and transparency. Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email careers@fluidstack.io with your resume/CV, the role you've applied for, and the date you submitted your application-- someone from our recruiting team will be in touch.
Sales Enablement Lead
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE We're seeking a seasoned enablement builder-operator to take on a foundational role in standing up GTM Enablement as Fireworks scales its go-to-market motion. The role sits in the Revenue Operations organization and reports to the Head of GTM Enablement. As a Principal GTM Enablement Manager, you'll co-develop and co-deliver Firecademy, our monthly in-person onboarding program, with an eye toward full ownership over time. You'll also lay the foundation for role-based ramp journeys that get every Account Executive, AI Field Engineer, and BDR productive fast. And you'll support the ongoing readiness that keeps our field ahead of the pace of product innovation and industry evolution. You bring the fundamentals of great enablement: deep facilitation and content-building chops, strong program management, fluency across sales methodologies, and excellent stakeholder management. As our on-site point of contact in San Mateo, you'll partner closely with Product, Marketing, and Sales Leadership to turn a rapidly evolving product into field readiness. And you'll go further than most enablers: you build the tools you teach, with hands-on experience creating AI agents that lift seller efficiency. Please Note: This is initially an individual contributor role reporting to the Head of GTM Enablement. It follows the San Mateo in-office policy (Monday/Wednesday/Friday), plus full weeks during the monthly Firecademy onboarding program. WHAT YOU'LL OWN 1. Develop & Deliver Firecademy and role-based ramp: Co-develop and co-deliver Firecademy, our monthly in-person onboarding program, with the intention of full ownership within the first 6 months. Lay the foundation for the role-based ramp journey, spanning live trainings, eLearnings, and manager-led activities, with role-specific paths so every new Account Executive, AI Field Engineer, and BDR ramps consistently and productively. 2. Build and deliver enablement content and programs: Design and deliver novel training programs with subject-matter experts across product knowledge, sales skills, competitive positioning, and internal process, and facilitate high-impact live and virtual sessions for audiences from new ICs to senior leaders in support of ongoing enablement across the AI Native and Enterprise segments. Partner with Product and Marketing to translate new product primitives into field-ready enablement, and lead the execution of critical GTM programs alongside cross-functional leaders across Sales, Field Engineering, Marketing, and Product. 3. Codify field best practices and influence the GTM motion: Synthesize ground truth from real customer engagements and enablement outcomes to surface and codify best practices, deliver them to the field, and feed insight upstream to shape the evolving GTM motion. Represent enablement to senior GTM and Revenue Operations leadership with clear read-outs on progress, gaps, and impact. 4. Help define the future of agentic enablement: Shape what agentic enablement looks like at Fireworks, designing and shipping AI agents that lift Account Executive efficiency and surface Revenue Operations insight, building on the foundations laid by our GTM Engineering team. MINIMUM QUALIFICATIONS - 10+ years of total experience across GTM enablement, sales, or solutions roles (2+ years within Enablement) - Built enablement and onboarding programs from scratch, not inherited and maintained - Elite at both content development and live facilitation (multi-day sessions to groups of 20 or more), and a trusted cross-functional partner to senior GTM leadership - Has personally built AI agents or apps, deployed at scale, to drive seller or operations productivity, through prompting, no-code, low-code, or code (engineering degree not required) - Proven ability to enable technical sellers to sell credibly to technical buyers - Fluency across multiple sales methodologies, not dependent on any single named framework - Thrives in ambiguity, extreme ownership, and the pace of a high-growth startup - Based in the San Mateo area and able to meet the in-office policy PREFERRED QUALIFICATIONS - Prior experience as a quota-carrying field IC (Account Executive, AI Field Engineer, or similar) - Experience leading or managing a GTM team - Background in AI/ML infrastructure, developer tools, or API-first and consumption-based businesses, with literacy in usage-based pricing models - Familiarity with modern enablement tooling and systems (LMS, CMS, CRM, and enablement platforms) WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Partnerships Lead
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. ABOUT THE ROLE We're hiring a high-ownership sales operator to drive sourced pipeline and revenue through the Microsoft Azure channel. This is a quota-carrying, field-facing role. You'll map Microsoft's ISV and enterprise field org, activate co-sell motions with the right PDMs and AEs, and build the repeatable sales plays that move customers to Fireworks AI through Azure Foundry. You'll own the forecast and the number. The playbook doesn't fully exist yet. You'll have real influence over how we engage Microsoft's field teams, what good looks like for partner-sourced pipeline, and how we build a co-sell motion that scales across ISV and enterprise segments. If you thrive when you're creating from scratch and can hold yourself accountable to a number while doing it, this is the role. WHAT YOU'LL OWN Pipeline and revenue - Source and own a pipeline target through the Microsoft Azure channel - Co-sell qualified opportunities with Microsoft ISV and enterprise AEs and PDMs - Run weekly forecasting cadences with accurate CRM hygiene and clear escalation visibility Team mapping and stakeholder management - Build and maintain a living map of Microsoft's field org across ISV and enterprise-facing teams - who owns which accounts, who moves deals, who has co-sell budget - Develop working relationships with PDMs, field AEs, and ISV partner managers at Microsoft - Serve as Fireworks AI's primary point of contact for joint business reviews, pipeline reviews, and co-sell coordination Sales plays and enablement - Develop sales plays tailored to the ISV and enterprise motion - positioning Fireworks AI's inference platform against the decision criteria that matter in each segment - Build and deliver enablement for Microsoft field sellers on Fireworks AI: clear, crisp positioning they can use in front of customers without a technical translator - Design the intake, escalation, and co-sell workflows that keep deals from stalling Joint planning and operations - Own joint business planning with Microsoft counterparts: territory plans, account maps, co-sell targets, and QBR cadences - Coordinate co-marketing moments (joint events, solution briefs, field plays) that generate ISV and enterprise pipeline - Surface field intelligence from Microsoft conversations back to Fireworks AI's product and GTM teams YOU'RE A GOOD FIT IF YOU - Have 7+ years in GTM, partnerships, or field sales at a technology company - and a track record of operating fast when the environment changes - Know how Microsoft's field org actually works: account teams, SSPs, GBBs, marketplace mechanics, co-sell programs, MACC spend, partner incentives - and how to activate them at the deal level - Build systems, not just run plays. You document the motion, create the playbooks, and make it repeatable - Are comfortable owning a number before all the conditions are perfect, and stay accountable on pipeline sourcing, progression, forecasting - Can communicate clearly and concisely - you translate complex platform capabilities into a value story a non-technical field seller can use in front of a customer - Hold yourself accountable to pipeline hygiene and forecast accuracy - not just relationship depth THE TECHNICAL BAR This is not an engineering role. But it requires genuine curiosity about how AI inference platforms work. You'll need working fluency in model serving, inference optimization, and AI training infrastructure - enough to speak credibly about why Fireworks AI's platform matters to ISVs and enterprises evaluating options in the market. If you don't have that fluency today, you can build it here - we'll help. What you can't be is someone who deflects every technical question or can't hold a credible 30-minute conversation with a solutions architect or a technical evaluator. The through-line: you need to understand what we do well enough to translate it for someone who doesn't. That's the bar. NICE TO HAVE - Experience working at or within a hyperscaler partner ecosystem (Microsoft, AWS, GCP) - Experience selling or partnering in AI/ML infrastructure, model serving, or MLOps - Experience working with ISVs at the platform layer - understanding their build-vs-buy decisions and procurement dynamics - Non-linear career path - varied, scrappy backgrounds carry real weight here WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
MTS, Security
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE: Security is the foundation of trust in AI systems. As the Security Engineer at Fireworks AI, you will play a key role in designing, implementing and operating security controls across AI infrastructure, AI platforms and internal systems. You will work closely with the multiple teams to strengthen our security posture and support our rapid growth. As more organizations rely on large language models and cloud-native AI services, ensuring the confidentiality, integrity, and availability of data, models, and infrastructure is paramount. This role plays a critical part in building that trust by designing and embedding security across layers of our technology stack. KEY RESPONSIBILITIES: - Design and build security-focused software and platform capabilities to protect customer data, models, and services across our multi-cloud infrastructure, including encryption, identity and access management, secure API gateways, secure model execution, and sandboxing strategies. - Perform security reviews of cloud-native architectures—including Kubernetes clusters, multi-cloud workloads, and distributed data stores—and build integrated systems for continuous security monitoring, anomaly detection, and automated response. - Embed security into CI/CD pipelines using a DevSecOps approach, implementing automated scanning, policy enforcement, and secure-by-default build and deployment workflows. - Apply a build-over-buy philosophy by designing and developing in-house security tooling and automation where it provides better control, scalability, and integration than off-the-shelf solutions. - Build and operate a comprehensive vulnerability management program, partnering with various teams to remediate risks across applications, containers, cloud infrastructure, and dependencies. - Operate and continuously improve security operations, including detection engineering, alert triage, incident response, and continuous improvement through post-incident reviews. - Participate in red/blue team exercises, tabletop simulations, and post-incident root cause analysis to strengthen security resilience. - Embed compliance and regulatory controls into infrastructure and product layers (e.g., SOC 2, ISO 27001, ISO42001, HIPAA, PCI-DSS, GDPR). MINIMUM QUALIFICATIONS: - 3 to 7 years of experience in software engineering or security engineering with a strong focus on security, infrastructure, or cloud-native systems. - Proficient in Python and/or Go with experience in designing production-grade systems. - Strong understanding of cloud-native architectures using GCP, particularly in the area of network segregation, authentication, authorization, encryption, data protection, intrusion detection, and cloud-specific security benchmarks. - Hands-on experience with Kubernetes, Docker, and containerized production environments; deep knowledge of Kubernetes internals and native security controls is a strong plus. - Familiarity with security tooling in managed CI/CD environments (e.g., GitHub Actions, Harness, CircleCI). - Solid experience working in Linux environments, including system administration, debugging, and automation via command-line tooling. - Familiarity with modern identity and access controls (SAML, OAuth, OIDC, SSO, RBAC/ABAC). PREFERRED QUALIFICATIONS: - Experience designing secure multi-cloud deployments and zero-trust architectures. - Experience designing, operating, and securing large-scale Kubernetes platforms, including control plane security, node hardening, and multi-tenant isolation. - Experience designing, operating, and securing large-scale multi-cloud platforms across AWS, GCP, Azure, Oracle Cloud, and GPU as service cloud providers. - Proficiency with infrastructure-as-code using Terraform and Python, including experience building modular policy-as-code frameworks. - Strong understanding of data protection techniques, including encryption at rest/in transit, tokenization, key management, and confidential computing. - Experience integrating security into microservice architectures, service meshes, and distributed systems. - Hands-on experience securing LLM/ML platforms, model inference infrastructure, GPU clusters, or data labeling pipelines. - Experience designing detection engineering pipelines across cloud audit logs, network telemetry, and application signals. - Experience building large-scale IAM and PAM platforms using least-privilege, workload identity, and just-in-time access. - Familiarity with container image vulnerability remediation, security, SBOM generation, and software supply chain security. - Experience building, implementing and operating security automation platforms for incident response and security operations. - Familiarity with compliance tooling and frameworks (e.g., Vanta, SOC 2, ISO 27001, ISO 42001, PCI-DSS). WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Member of Technical Staff, Enterprise Foundations
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE Enterprise Foundations builds the capabilities the largest companies in the world need before they can run their business on Fireworks. Global banks, insurers, healthcare and legal technology companies, and large-scale SaaS platforms are moving AI into production now, and they arrive with requirements that only apply to scaled companies: how their organization and users are modeled, who is allowed to do what, how usage is metered and billed, what gets logged, where data lives and who holds the keys, and whether the whole thing can run inside their own cloud. You will own that work as end-to-end features. A single project routinely starts in a customer conversation, becomes a change to a core data model or API, and then has to be threaded through the control plane, the training and inference stacks, the SDK and CLI, and the console before it counts as shipped. Much of what we build is a foundational shift rather than an addition: a new primitive that other teams' code has to move onto, rolled out against live production traffic without breaking anyone. The work sits close to revenue. Requirements come out of live enterprise deals, security reviews, and customer conversations. You will be in those rooms, decide what product becomes, and go build it. WHAT YOU'LL DO - Own foundational capabilities end to end — data model and API through control plane, runtime, SDK/CLI, and console — and migrate live systems onto them - Design the primitives large customers organize around — organizations and sub-accounts, groups, roles, service identities — and connect them to enterprise directories through federation and provisioning (SSO, SCIM) - Design multi-tenant authorization, policy enforcement, and audit systems that hold up in front of a security architect - Make usage metering, spend controls, and billing correct and legible at scale — customers reconcile our numbers against their own - Own data isolation and key management — customer-managed encryption keys across AWS, GCP, and Azure — threaded through datasets, fine-tuning, RL, checkpoints, models, and inference - Deploy and operate Fireworks inside a customer's own cloud, and solve data residency and regional isolation for customers with hard constraints - Use AI tooling aggressively — we expect you to automate yourself YOU MIGHT BE A FIT IF - You want your work measured in unblocked revenue, not tickets closed - You're comfortable owning domains you've never worked in before - You want the whole problem — data model through UI — and don't need someone else to draw the edges for you - You can hold your own with an enterprise security architect - You'd rather ship what closes the deal than perfect the abstraction - You treat ambiguity as the job, not a complaint about the job MINIMUM QUALIFICATIONS - 4+ years building and operating production backend or distributed systems at scale - Strong server-side engineering skills in Go, Python, C++, TypeScript, or similar, and willingness to work outside your primary layer to land a feature - Experience designing APIs and data models that other teams build on, and evolving them under live traffic without breaking callers - Hands-on depth in at least one major cloud (AWS, GCP, or Azure): IAM and workload identity, KMS, object storage, and VPC networking - A track record of owning an ambiguous, cross-team workstream from requirement through production - Willingness to work directly with customers PREFERRED QUALIFICATIONS - Enterprise identity and tenancy: SSO, SCIM provisioning, RBAC/ABAC, audit logging, and org modeling - Metering, quotas, or billing systems where correctness is customer-visible - Applied cryptography and key management: envelope encryption, KMS, and threat modeling - Kubernetes depth and infrastructure-as-code fluency (Terraform, GitOps) - Familiarity with LLM inference and fine-tuning — our work runs straight through the training and serving stacks, so it helps WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Business Development Representative (BDR), EMEA
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE We're looking for motivated and tech-savvy Business Development Representatives (BDRs) with a strong interest in AI to join our growing sales team. In this role, you’ll play a key part in building a healthy pipeline for our Account Executives by qualifying inbound leads and proactively prospecting into high-value target accounts. This is an opportunity to be at the frontlines of a fast-moving AI company, engaging in thoughtful, technical conversations with a knowledgeable customer base. The ideal candidate is results driven, exhibits strong intellectual curiosity of the evolving AI space, and can operate in a fast-paced, highly-dynamic start up environment. You should be comfortable initiating outreach, handling nuanced product discussions, and helping prospects understand the impact of generative AI on their business. KEY RESPONSIBILITIES - Strategically prospect into key accounts across email, calling and Linkedin, communicating Fireworks AI’s unique value proposition - Consistently meet new business opportunity and pipeline generation targets - Craft personalized, tailored outreach through various research methods to prioritize the right accounts and prospects - Qualify and engage inbound leads, ensuring a smooth transition to our Account Executive team - Act as a brand ambassador, educating prospects on the power and potential of our inference solutions - Collaborate with Sales and Marketing to refine messaging and outreach strategies based on market feedback - Stay current on AI/ML trends to conduct informed, relevant conversations with technical and business audiences MINIMUM QUALIFICATIONS - 1-2+ years of experience as a BDR/SDR - Bachelor’s degree or equivalent practical experience - Demonstrated interest in technology sales, with a strong interest AI and machine learning - Excellent communication and interpersonal skills; able to engage confidently with technical stakeholders - Self-motivated and organized, with the ability to manage multiple priorities in a fast-paced environment PREFERRED QUALIFICATIONS - Previous startup or entrepreneurial experience, with a proactive and adaptable mindset - Prior experience in a customer facing role, ideally in SaaS, AI, or emerging tech - Familiarity with CRM systems and sales engagement tools (e.g., Salesforce, Outreach, Apollo, etc.) - Degree in engineering, computer science, or a related technical field - Active interest in AI/tech communities with a demonstrated commitment to continuous learning in the space Fireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided. WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Business Development Representative (BDR)
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE We're looking for motivated and tech-savvy Business Development Representatives (BDRs) with a strong interest in AI to join our growing sales team. In this role, you’ll play a key part in building a healthy pipeline for our Account Executives by qualifying inbound leads and proactively prospecting into high-value target accounts. This is an opportunity to be at the frontlines of a fast-moving AI company, engaging in thoughtful, technical conversations with a knowledgeable customer base. The ideal candidate is results driven, exhibits strong intellectual curiosity of the evolving AI space, and can operate in a fast-paced, highly-dynamic start up environment. You should be comfortable initiating outreach, handling nuanced product discussions, and helping prospects understand the impact of generative AI on their business. KEY RESPONSIBILITIES - Strategically prospect into key accounts across email, calling and Linkedin, communicating Fireworks AI’s unique value proposition - Consistently meet new business opportunity and pipeline generation targets - Craft personalized, tailored outreach through various research methods to prioritize the right accounts and prospects - Qualify and engage inbound leads, ensuring a smooth transition to our Account Executive team - Act as a brand ambassador, educating prospects on the power and potential of our inference solutions - Collaborate with Sales and Marketing to refine messaging and outreach strategies based on market feedback - Stay current on AI/ML trends to conduct informed, relevant conversations with technical and business audiences MINIMUM QUALIFICATIONS - Bachelor’s degree or equivalent practical experience - Demonstrated interest in technology sales, with a strong interest AI and machine learning - Excellent communication and interpersonal skills; able to engage confidently with technical stakeholders - Self-motivated and organized, with the ability to manage multiple priorities in a fast-paced environment PREFERRED QUALIFICATIONS - Previous startup or entrepreneurial experience, with a proactive and adaptable mindset - Prior experience in a customer facing role, ideally in SaaS, AI, or emerging tech - Familiarity with CRM systems and sales engagement tools (e.g., Salesforce, Outreach, Apollo, etc.) - Degree in engineering, computer science, or a related technical field - Active interest in AI/tech communities with a demonstrated commitment to continuous learning in the space Fireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. The estimated range for total on target earnings (including base salary and on target incentive pay) for candidates in the San Francisco/New York City Area for this role is $85,000 - $100,000 per year. WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
AI Factory Partnerships Lead - OEM & Infrastructur...
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. About the role Enterprises are standing up AI factories: full-stack, on-prem and colocated deployments of compute, networking, storage, and models. Today they assemble that stack themselves and figure out the software layer on their own. We're hiring a Partnerships Lead to collapse it into a single, pre-integrated bundle. You'll assemble alliances across OEMs (Dell, HPE, and others), silicon (NVIDIA and others), packaged with Fireworks as the operating system on top. You'll own the bundle definition, joint pricing, go-to-market plan end to end, from first alliance conversation to repeatable revenue. The playbook doesn't exist yet. You'll write it: which OEM to lead with, how to structure the commercial stack, and what the joint reference architecture looks like. If you want to define the AI factory category rather than inherit one, this is the role. What you'll own Bundle construction - Build alliances across the stack - Define the reference bundle with Fireworks as the serving and orchestration layer - Validate joint architectures with Fireworks engineering - Structure and negotiate the commercial agreements Go-to-market and execution - Build and execute the joint GTM plan: ICP, field plays, targets - Enable field sellers on joint offering - Drive deals end to end with partner sellers and own the forecast You're a good fit if you have - 10+ years in enterprise infrastructure, with at least one joint offering you built and scaled - Key relationships inside at least two of: Dell, HPE, NVIDIA, AMD, or equivalent OEM - Understand the AI factory stack - Experience in integrated offerings (appliance or validated design programs) Nice to have - Background selling into on-prem or sovereign AI deployments, where the customer runs the hardware and the vendor runs the software - Familiarity with LLM inference economics: throughput per GPU, utilization, and why the software layer determines the ROI of the whole bundle WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
AI Deployment Strategist (EMEA)
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE: As an AI Deployment Strategist, you are the long-term owner of our most important customer accounts. You pair with Account Executives to close: scoping pilots, setting success criteria, and running the technical side of the commercial conversation. At signature, you take the account and stay on it, driving adoption and expansion over years rather than quarters, so AEs can move to the next deal. This role suits entrepreneurial, technically credible operators; founder and founder CEO backgrounds are a strong fit. What we value most is first principles thinking: reasoning about unfamiliar problems from the ground up rather than from playbooks. You will be evaluated on this directly in the interview process, and strength here can outweigh gaps elsewhere in your background. KEY RESPONSIBILITIES: - Account Ownership: Own the customer relationship and commercial outcome from signature onward, including adoption, expansion, and renewals. - Deal Support: Partner with AEs pre-signature on pilot scoping, success criteria, and technical-commercial framing. - Delivery Cadence: Run the operating rhythm of the account across the customer's and Fireworks' teams (FDEs, AMLEs, product, support). - Value Realization: Translate customer goals into concrete deployment milestones and make sure they land. - Expansion Strategy: Identify and drive new workloads, teams, and use cases within existing accounts. - Voice of Customer: Represent account needs internally with enough technical precision to be actionable. MINIMUM QUALIFICATIONS: - First principles and critical thinking: the ability to break down novel problems and reason to a solution without a reference implementation. This is the primary interview signal and can outweigh other qualifications. - Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent technical depth. - 3+ years in roles combining technical substance with commercial ownership (deployment strategy, technical consulting, founder, forward deployed, or similar). - Strong technical credibility: able to hold your own with customer engineering leadership and our field engineers, and to reason about AI infrastructure tradeoffs. - Track record of owning outcomes over long horizons, not handing off after the sale. - Excellent judgment, communication, and stakeholder management with senior audiences. PREFERRED QUALIFICATIONS: - Founder or founding team experience, especially as CEO or commercial lead of a technical product. - Experience deploying or operating AI/ML products in production with enterprise customers. - Experience navigating enterprise constraints in EMEA (procurement, data residency, GDPR, EU AI Act). - Experience in a startup or fast-paced environment. WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Research / Software Engineer - Humanoid Whole Body...
FieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment. Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use. FieldAI is seeking a Software/Research Engineer to help build the learning systems that power our next generation of humanoid robots. You'll work across whole-body loco-manipulation, reinforcement learning, motion retargeting, and real-world robot deployment, turning new research and technical developments into reliable capabilities on physical humanoids. This is a highly hands-on role for someone excited about closing the loop between research, simulation, and robots operating in the real world. What You Will Get To Do Develop and train whole-body loco-manipulation policies for humanoid robots. Deploy trained policies to physical humanoids and integrate them into our production software stack. Advance our motion retargeting pipeline, transforming human motion into physically plausible, robot-executable behaviors that interact with diverse environments and objects. Reduce the sim-to-real gap by improving simulation fidelity and closing the real-to-sim loop, using real-world robot data to calibrate and refine our simulators. Build automated evaluation and validation systems that make it faster and more reliable to move policies from simulation onto physical robots. Improve the performance and scalability of our robot-learning infrastructure, enabling faster experimentation and policy iteration. Work closely with researchers and engineers across perception, learning, simulation, and hardware to turn new ideas into deployed robot capabilities. What You Bring BS, MS, or PhD in Robotics, Computer Science, Machine Learning, Engineering, or a related field, or equivalent experience. Experience with reinforcement learning, imitation learning, generative models, or other learning-based approaches for robotics. Strong understanding of robotics fundamentals such as kinematics, dynamics, control, and physical interaction. Experience developing and evaluating robotic systems in simulation and/or on physical hardware. Ability to move comfortably between research experimentation and production-quality engineering. What Will Set You Apart Hands-on experience with humanoid robots. Experience with whole-body loco-manipulation. Experience with GPU-accelerated simulation frameworks such as NVIDIA Isaac Sim, Isaac Lab, and/or Newton. Experience with motion retargeting. Experience taking learned robot behaviors from simulation to real hardware. Experience building scalable RL training, evaluation, and/or automated robot-testing infrastructure.
Lead Computer Vision Engineer
WHY FACULTY? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here https://faculty.ai/impact. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. ABOUT THE TEAM Our Defence team is focused on building and embedding human-centered AI solutions which give our nation a competitive edge in the defence sector. We collaborate with our clients to bring ethical, reliable and cutting-edge AI to high-stakes situations and maintain the balance of global powers essential to our liberty. Because of the nature of the work we do with our Defence clients, you will need to be eligible for UK Security Clearance (SC) and willing to work between 2 to 4 days per week on-site with these customers which may require travel to locations throughout the UK. When not required on client sites, you’ll have the flexibility to work from our London office or remotely from elsewhere within the UK. ABOUT THE ROLE We are seeking a visionary Computer Vision (CV) Specialist to lead our most ambitious AI initiatives within the defence sector. Bridging the gap between cutting-edge research and real-world deployment, you will act as a primary technical authority, architecting sophisticated CV systems that solve critical customer challenges. This is an entrepreneurial opportunity to shape our technical strategy, drive capability development, and represent the business unit as a thought leader. If you thrive on autonomy and want to push the boundaries of applying State-of-the-Art (SOTA) technology, this role offers the platform to make a definitive impact. WHAT YOU'LL BE DOING: - Delivering high impact, hands-on computer vision work and architecting technical solutions for complex project requirements. - Leading the technical delivery of CV projects and providing expert guidance to multidisciplinary teams throughout the development lifecycle. - Winning new business by contributing expert CV insight to bids and identifying opportunities to integrate advanced visual intelligence into customer solutions. - Staying at the forefront of the field by mastering SOTA developments and sharing best practices across the business unit to maintain a competitive edge. - Representing the organisation both internally and externally as an authoritative voice and subject matter expert in computer vision. - Partnering with leadership to define the technical strategy for CV work and taking ownership of capability development within the Defence domain. - Mentoring and developing talented team members who share an interest in CV, fostering an environment of continuous learning and technical excellence. WHO WE'RE LOOKING FOR: - You possess a deep understanding of State-of-the-Art Computer VisionAI approaches and feel confident applying both machine learning and classical computer vision techniques to real-world problems. - You are an experienced technical leader who enjoys the challenge of guiding teams and turning real world problems into architecting system architectures with minimal oversight. - You have a proven track record of deploying CV models into production environments and navigating the practicalities of real-world deployment, performance and latency. - You bring a collaborative and entrepreneurial mindset, with the ability to communicate technical concepts effectively to both specialist colleagues and non-technical clients. - Your background includes meaningful experience in Python, including object-oriented programming, and you are comfortable exploring low-level components when necessary. - You are passionate about capability building, whether through developing R&D accelerators or helping others sharpen their technical skills through mentorship. THE INTERVIEW PROCESS 1. Talent Team Screen (30 minutes) 2. Introduction to the team (30 minutes) 3. Technical Interview (90 minutes) 4. Commercial Interview (60 minutes) OUR RECRUITMENT ETHOS We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations. If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours. A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
Data Scientist
WHY FACULTY? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here https://faculty.ai/impact. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. ABOUT THE TEAM Our Defence team is focused on building and embedding human-centered AI solutions which give our nation a competitive edge in the defence sector. We collaborate with our clients to bring ethical, reliable and cutting-edge AI to high-stakes situations and maintain the balance of global powers essential to our liberty. Because of the nature of the work we do with our Defence clients, you will need to be eligible for UK Security Clearance (SC) and willing to work between 2 to 4 days per week on-site with these customers which may require travel to locations throughout the UK. When not required on client sites, you’ll have the flexibility to work from our London office or remotely from elsewhere within the UK. ABOUT THE ROLE: As a Data Scientist, you will work closely with clients and cross functional teams to define project scope, ensure technical feasibility, and drive delivery excellence. You’ll design and deliver bespoke data science solutions, shaping the technical direction of high-impact projects and solidifying our reputation as a leader in practical, measurable AI. WHAT YOU'LL BE DOING: - Mapping the end-to-end data science approach and designing the associated software architecture for projects - Driving the technical scoping and feasibility assessment of new projects - Building strong client relationships by acting as a technical advisor and shaping the direction of current and future engagements - Delivering bespoke algorithms and scalable software solutions that adhere to best practices for high-stakes decision-making - Setting the technical bar for the project team, ensuring the highest standards of code, rigour, and delivery quality (IC leadership) - Contributing to Faculty's thought leadership and reputation through teaching, public speaking, or open-source projects WHO WE'RE LOOKING FOR: - You have proven experience in a professional data science or quantitative academic role, underpinned by high mathematical and statistical competence. - You are a strong Python programmer, proficient in essential libraries (NumPy, Pandas) and a deep-learning framework (TensorFlow/PyTorch). - You possess a solid grasp of core data science techniques (supervised/unsupervised learning, time-series, NLP, model validation) and the ability to innovate new algorithms. - You apply a rigorous scientific and entrepreneurial mindset, translating complex business problems into a mathematical framework and measuring model impact upon deployment. - You are an exceptional communicator, adept at translating complex technical solutions into persuasive, actionable insights for senior and non-technical audiences. - You contribute to team success by project planning, assessing technical feasibility, estimating delivery timelines, and achieving measurable outcomes. OUR INTERVIEW PROCESS 1. Talent Team Screen (30 minutes) 2. Take Home Technical Assessment 3. Technical Interview (90 minutes) 4. Commercial Interview (60 minutes) OUR RECRUITMENT ETHOS We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations. If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours. A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
Inference Software Engineer
About Etched Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history. Key responsibilities - Support porting state-of-the-art models to our architecture. Help build programming abstractions and testing capabilities to rapidly iterate on model porting. - Build, enhance, and scale our runtime, including multi-node inference, intra-node execution, state management, and robust error handling. - Optimize routing and communication layers using our collectives. - Utilize performance profiling and debugging tools to identify bottlenecks and correctness issues. You may be a good fit if you have - Proficiency in C++ or Rust. - Understanding of performance-sensitive or complex distributed software systems like Linux internals, accelerator architectures (e.g. GPUs, TPUs), Compilers, or high-speed interconnects (e.g. NVLink, InfiniBand). - Familiarity with PyTorch or JAX. - Ported applications to non-standard accelerator hardware or hardware platforms. Strong candidates may also have experience with (Nice-to-have qualifications) - Developed low-latency, high-performance applications using both kernel-level and user-space networking stacks. - Deep understanding of distributed systems concepts, algorithms, and challenges, including consensus protocols, consistency models, and communication patterns. - Solid grasp of Transformer architectures, particularly Mixture-of-Experts (MoE). - Built applications with extensive SIMD (Single Instruction, Multiple Data) optimizations for performance-critical paths. Benefits - Medical, dental, and vision packages with generous premium coverage - $500 per month credit for waiving medical benefits - Housing subsidy of $2.5k per month for those living within walking distance of the office - Relocation support for those moving to San Jose (Santana Row) - Various wellness benefits covering fitness, mental health, and more - Daily lunch + dinner in our office - Unlimited compute budget subject to ROI justification How we’re different Etched believes in the Bitter Lesson http://www.incompleteideas.net/IncIdeas/BitterLesson.html. We are the first inference-focused frontier AI system. Our addressable market is the entirety of inference, unlike many of our competitors. We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.
Applied AI Engineer, Manufacturing Execution
About Etched Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history. Job Summary We are using AI to build and ship AI hardware. Etched’s production ramp requires thousands of interdependent, chained decisions that involve product configurations, material availability, production capacity, capital commitments, complex logistics, field deployments, customer commitments, and more. You will embed with Platform, Production, Supply Chain, Finance, and manufacturing partners to build the agentic systems that make those decisions faster and better. You will own the development of agentic systems that loop signal to execution: understanding what Etched needs to manufacture and deliver; modelling production plans and scenarios; triaging changes and the unexpected; capturing decisions in the systems we execute through - and designing agents that augment and scale our teams. Success is measured by what we deliver, the schedules we attain, our ramp speed, and time from signal to action. Production is the product. Etched offers a unique environment to tackle real supply-chain challenges and production decisions with frontier model capabilities: we have our own in-office cluster to run agentic systems on, all teams are in-person, and every cluster we deploy offers an opportunity to raise the bar across production. You will build the frontier systems that help us coordinate execution and learn from every build. Key responsibilities - Build, deploy, and operate AI systems that run S&OP, material planning, build readiness, manufacturing partner execution, quality, logistics, and customer deployments. - Embed with Platform, Production, Supply Chain, Finance, and other teams to identify high-leverage decisions, turn them into executable workflows augmented by agentic systems, and own outcomes. - Build operational models connecting demand, product configurations, revisions, BOMs, supply, inventory, cost, capacity, builds, tests, quality, and shipments. - Build agents that craft executable plans considering demand, supply, capacity, inventory, capital, schedules, and risk - and keep those plans current as constraints change. - Propagate design changes through material exposure, sourcing, cost, factory and test readiness, production schedules, and delivery commitments. - Build production and quality agents that coordinate clear-to-build, work in progress, bottlenecks, testing, excursions, genealogy, containment, root-cause analysis, and corrective action. - Design historical replays and live evals tied to operating outcomes including forecast quality, schedule attainment, inventory, cost, yield, throughput, and resolution time. - Continuously evaluate frontier models and system optimization methods. You may be a good fit if you have - A track record of solving hard problems across stacks and domains. You enjoy being dropped into unfamiliar territory and figuring it out - Comfort with Python and code: you can read it, modify it, debug it, and direct AI to write it well. We do not care whether you write code from scratch. We care whether you ship things that work - Fluency using AI to learn and ramp on new problems; agentic coding tools, deep research, and frontier models are how you work, not an add-on - Hands-on experience building and shipping LLM-based agents or AI tooling that real users depend on (beyond just calling an AP - context engineering, tool integration, orchestration, failure analysis) - An eval-driven mindset: you measure whether AI systems actually work before scaling them - High agency and comfort with ambiguity. You can find the problem, not just solve the stated one - Worked in complex hardware, manufacturing, supply chain, S&OP, operations research, or enterprise planning, ideally through periods of hyperscale Strong candidates may also have experience with - ERP/MRP, PLM, MES, and/or QMS - BOMs and ECOs, NPI and ramp, factory test, or quality systems - Forecasting, constraint optimization, simulation, or digital twins Benefits - Medical, dental, and vision packages with generous premium coverage - $500 per month credit for waiving medical benefits - Housing subsidy of $2,500 per month for those living within walking distance of the office - Relocation support for those moving to San Jose (Santana Row) - Various wellness benefits covering fitness, mental health, and more - Daily lunch and dinner in our office - Unlimited compute budget subject to ROI justification How we’re different Etched believes in the Bitter Lesson http://www.incompleteideas.net/IncIdeas/BitterLesson.html. We are the first inference-focused frontier AI system. Our addressable market is the entirety of inference, unlike many of our competitors. We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.
Solutions Engineer
About us Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator. The role As a Solutions Engineer at Encord, you will be the core technical expert and problem-solver for our most complex customers. You are the engineering-focused counterpart to the commercial team, partnering with Account Executives to architect and implement solutions for prospects on the cutting-edge of AI. You will be the expert on how our platform integrates and scales, establishing technical credibility and guiding prospects through complex evaluations, especially for applications in robotics, autonomous systems, and multimodal AI. You are both a deep technical builder and an expert business value translator. What you'll do - Partner with Account Executives and the ML team to lead the technical strategy for complex, enterprise sales cycles and co-own the technical win - Lead deep technical discovery sessions with a wide range of stakeholders (from ML Engineers to MLOps leaders) to not only uncover business pain but to architect a complete technical solution and integration path - Architect, build, and deliver highly-technical, customised product demonstrations and proof-of-concepts (POCs) that solve specific, complex customer problems - Own the end-to-end technical implementation of POCs, writing robust, production-quality Python scripts for complex data ingestion, pre/post-processing, dataset management, and custom platform integrations - Act as the key technical advisor to prospects, expertly guiding them through security, architecture, and integration evaluations, particularly on complex data pipelines involving multimodal data, LiDAR, or robotics sensor data - Translate complex technical architectures and findings into clear, persuasive value propositions for senior, non-technical stakeholders (Directors, VPs, CTOs) - Serve as the "voice of the customer" to our Product and Engineering teams, channelling detailed, technical feedback from complex enterprise clients to help shape the product roadmap Who we're looking for - Coding experience — hands-on experience building and debugging scripts and solutions using Python or other scripting languages; experience with SDKs is desirable - Excellent communication and presentation skills — you can confidently command a room of engineers and just as easily simplify complex concepts for senior decision-makers - Strong technical command of modern cloud infrastructure (GCP, AWS, Azure) and machine learning concepts - A "hacker mindset" with a strong engineering foundation: you are a creative problem-solver who builds robust, scalable, and efficient scripts and integration workflows to overcome technical hurdles - A solution-driven and customer-obsessed mindset — while you understand commercial goals, your passion is for solving complex technical problems and ensuring customer success - Ability to translate value between technical and commercial stakeholders, both with prospects and internally within Encord - Bonus: hands-on experience working with multimodal AI, sensor-fusion, physical AI, LiDAR data, or in the robotics industry Experience requirements - 1 - 5+ years of experience in a customer-facing role within an AI business, such as Solutions Engineering, Solutions Architecture, or Technical Account Management - Proficiency in Python, with the ability to write clean, production-quality scripts for data ingestion, pipeline automation, API integrations, and custom tooling; experience with REST APIs and SDKs is strongly preferred - Hands-on experience with at least one major cloud platform (GCP, AWS, or Azure), including data storage, compute, and deployment patterns common in ML workflows - Solid understanding of machine learning concepts and the ML development lifecycle — from data preparation and annotation through model training, evaluation, and deployment - Demonstrated ability to lead technical discovery, architect integration solutions, and own end-to-end POC delivery in a complex enterprise sales environment - Proven track record of earning trust with highly technical audiences (ML engineers, MLOps, data engineers) while communicating value clearly to senior business stakeholders - Experience navigating enterprise security, compliance, and architecture reviews as part of a technical sales or implementation process - Prior experience in a high-growth start-up or scale-up strongly preferred - Bonus: Familiarity with multimodal data formats, LiDAR, robotics sensor data, or physical AI applications Why Encord - Competitive salary, commission, and meaningful equity in a high-growth start-up - Clear, accelerated growth opportunities as the company scales rapidly - Strong in-person culture: 4 days/week - Flexible PTO to fully recharge - Annual learning & development budget - Comprehensive health, dental, and vision coverage - Frequent travel opportunities across the U.S., London, and Europe - Bi-annual company offsites, twice-weekly team lunches, and monthly socials
Research Engineers, Post-Training
ABOUT DISTYL AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. WHAT WE ARE LOOKING FOR At Distyl, Research Engineers build the bridge between frontier AI research and production systems that deliver real business value. This role is for engineers who are excited to investigate how AI systems should be designed, rapidly prototype new ideas, and turn promising concepts into reliable systems that work inside real customer environments. Research Engineers operate at the intersection of applied research, systems engineering, and customer-facing deployment. They design and implement compound AI systems, run experiments to understand system behavior, build evaluation frameworks, and collaborate closely with AI Researchers, AI Engineers, and customer stakeholders. Their work is not limited to demos or isolated prototypes: they help turn new techniques into robust systems that can be measured, operated, and improved in production. KEY RESPONSIBILITIES - Design and run post-training workflows that improve the behavior, reliability, and usefulness of AI systems - Develop datasets, preference signals, evaluation suites, reward models, fine-tuning workflows, and feedback loops for applied AI use cases - Investigate how different post-training techniques affect system behavior across enterprise workflows and production constraints - Build infrastructure for experimentation, model comparison, regression testing, and behavior analysis - Partner with AI Researchers to explore new post-training methods and with AI Engineers to apply successful techniques in deployed systems - Analyze model outputs, failure modes, human feedback, and production traces to identify opportunities for behavioral improvement - Create repeatable processes for adapting AI systems to customer domains while preserving robustness, transparency, and maintainability - Communicate clearly with internal teams and customer stakeholders about model behavior, evaluation results, limitations, and tradeoffs WHO YOU ARE - Experience Improving Model Behavior: You have worked with fine-tuning, preference optimization, reinforcement learning, reward modeling, synthetic data, evals, or related post-training techniques - Strong Programming and Experimentation Skills: You can build training and evaluation pipelines, run controlled experiments, analyze results, and iterate quickly - Research-Oriented Builder: You care about understanding why behavior changes, not just whether a benchmark improves - AI Systems Mindset: You understand that model behavior is shaped by data, prompts, tools, retrieval, evaluators, and deployment context—not model weights alone - AI-Native Working Style: You use AI tools daily to accelerate coding, analysis, debugging, experimentation, and research exploration - Bias Towards Measurement: You make behavioral improvements concrete through evaluations, comparisons, regression tests, and production-relevant metrics - Comfort with Applied Constraints: You can balance research ambition with practical constraints around cost, latency, reliability, data availability, and customer requirements - Ownership Mentality: You take responsibility for whether post-training work improves real system outcomes, not just offline scores WHAT WE OFFER - The base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package - 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible time off - Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources - Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot - Complimentary in-office lunches and snacks provided - Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems - Ownership of high-impact projects across top enterprises - A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office. #LI-Hybrid We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.
Applied AI Researcher, Multi-Agent Systems
ABOUT DISTYL AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. WHAT WE ARE LOOKING FOR At Distyl we’re pushing the envelope of AI utilization in enterprise. This requires creative researchers who don’t just want to drive incremental improvements on benchmarks or optimize an existing process but instead are looking to creatively redefine how software is used. Our researchers come from many academic backgrounds but have strong research track records, operate in an AI-native way, and would be bored staying on the rails of a traditional research org. KEY RESPONSIBILITIES - The Multi-Agent Systems team focuses on designing architectures in which multiple agents coordinate to solve problems that require structured interaction across multiple reasoning processes. Researchers build systems that structure communication, route information, and coordinate decision-making across agents operating with different views of the problem - Researchers in Multi-Agent Systems investigate the interaction patterns that govern how agents collaborate. They study how agents exchange information, critique and refine each other’s reasoning, and coordinate execution across complex workflows. Their work identifies the mechanics behind effective communication, delegation, and coordination, in effect establishing the design language for how systems of agents can operate as cohesive, high-performing teams, with capabilities that arise from interaction rather than individual performance. WHAT WE REQUIRE - Built or studied systems where multiple agents collaborate through structured communication, delegation, critique, or iterative coordination. - Experience with agent orchestration, communication protocols, evaluator agents, or systems where multiple agents interact to exchange information, critique reasoning, and coordinate decisions over time - Experience with research in related fields, such as multi-agent reinforcement learning (MARL), graph neural networks (GNNs), knowledge graphs, mixed-initiative planning, etc. - Excited about making foundational advancements in how agents coordinate, reason and collaborate - Proven Track Record of Research Results: Whether you’ve published in top journals, posted amazing work on twitter, or somewhere else we want to see what you've done. - Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow. - Strong Programming and Data Analysis Skills: While you might not consider yourself a software engineer you need to be able to build prototypes of your ideas and then perform the experiments to prove the effectiveness to a F500 Head of AI. - Biases Towards Showing vs Telling: Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize. WHAT WE OFFER - The base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package - 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible time off - Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources - Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot - Complimentary in-office lunches and snacks provided - Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems - Ownership of high-impact projects across top enterprises - A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office. #LI-Hybrid We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.
Applied AI Researcher, Benchmarking
ABOUT DISTYL AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. WHAT WE ARE LOOKING FOR At Distyl we’re pushing the envelope of AI utilization in enterprise. This requires creative researchers who don’t just want to drive incremental improvements on benchmarks or optimize an existing process but instead are looking to creatively redefine how software is used. Our researchers come from many academic backgrounds but have strong research track records, operate in an AI-native way, and would be bored staying on the rails of a traditional research org. KEY RESPONSIBILITIES - The Benchmarking team defines how progress is measured. Researchers design evaluation frameworks that capture reasoning depth, interaction quality, reliability, and operational impact. They construct benchmarks that reflect real-world complexity. Their systems become the standard by which new architectures, techniques, and releases are judged. - Researchers in Benchmarking explore new paradigms for evaluating intelligent systems: adversarial robustness testing, longitudinal performance tracking, and human-in-the-loop assessment. They investigate how metrics shape model behavior and establish rigorous methodologies for quantifying emergent capability. Their insights drive both Distyl’s internal research priorities and industry-wide standards. WHO YOU ARE - Experience Designing and Running Evaluations: You’ve built or maintained benchmarks, test suites, or experimental frameworks to measure model or system performance - Statistical and Analytical Rigor: You design fair, reproducible experiments and can extract signal from noisy empirical results - Experience Building with Models, Not Just Building Models: We develop intelligent systems using models rather than training or fine-tuning them. Ideal candidates have expertise in compound AI systems, agentic collaboration, and associated techniques (ensembling, ReAct, graph-of-thoughts, etc.) - Proven Track Record of Research Results: Whether you’ve published in top journals, posted amazing work on twitter, or somewhere else we want to see what you've done - Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow - Strong Programming and Data Analysis Skills: While you might not consider yourself a software engineer you need to be able to build prototypes of your ideas and then perform the experiments to prove the effectiveness to a F500 Head of AI - Biases Towards Showing vs Telling: Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize WHAT WE OFFER - The base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package - 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible time off - Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources - Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot - Complimentary in-office lunches and snacks provided - Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems - Ownership of high-impact projects across top enterprises - A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office. #LI-Hybrid We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.
AI Strategist, Healthcare Solutions
ABOUT DISTYL AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. WHAT WE ARE LOOKING FOR As an AI Strategist, you'll lead and drive the technology solutions in Healthcare vertical and drive the GTM process with healthcare customer engagements, from first meeting to deal signed. You'll drive revenue and new logo expansion by diagnosing customer problems through an AI lens and designing data-driven, AI-enabled strategies that deliver desired outcomes and help prospective clients see the immediate value of AI adoption. As a core member of Distyl’s Healthcare GTM Team, you'll operate in 0→1 mode — rapidly building demos and proof-of-concept solutions that showcase the Distillery platform’s capabilities to prospective healthcare clients. You'll work at the intersection of business strategy and AI implementation, bridging the gap between Distyl’s technical AI tools and the business outcomes that get deals signed. Strong communication and storytelling skills are essential. You are the person in the room making the case for AI transformation. You'll also get hands-on — prototyping workflows on the Distillery platform, building demos in days not months, and collaborating with healthcare SMEs (clinicians, case managers, claims analysts) to ensure solutions address real operational pain points. This is a high-ownership role for someone who thrives at the intersection of AI strategy, analytics, and execution — and wants to build the GTM engine of an early-stage AI company from the ground up. KEY RESPONSIBILITIES - Drive the AI solutioning throughout the pre-sales process on healthcare deals — from initial discovery through deal close, you own the momentum that gets engagements across the finish line - Diagnose prospective client problems through an AI lens and identify where AI-enabled strategies can transform operations, optimize workflows, and improve outcomes at scale - Research clients and their industry landscape to prepare materials for prospective client meetings, including use case points of view tailored to each prospect - Develop deep expertise in Distyl’s Healthcare Solutions (Utilization Management, Care Management, Cost of Care, Claims, Member/Provider Communications etc.) to identify and prioritize high-value use cases for each customer - Feed insights to AEs to sharpen the pitch and differentiate Distyl’s AI-enabled offerings - Conduct technical discovery after Account Executives open the door — identify the right use cases, solution architecture, and feasibility - Identify the most valuable problems to solve. Embed yourself in the customer’s workflow to understand it better than the users themselves - Work closely with engineering to co-design solutions — you can whiteboard an architecture, debate tradeoffs in system design, and bridge the gap between what the customer needs and what the platform can deliver - Build demos and competitive positioning docs with internal stakeholders, driving rapid delivery for demos and POC scoping - Build out POC proposals — define scope, success criteria, timelines, and resource requirements - Navigate noisy enterprise data to identify how AI can create reliable outcomes despite real-world constraints - Build compelling storylines and decks that make the ROI of AI transformation concrete and undeniable - Create and maintain reusable GTM assets — demo scripts, ROI calculators, competitive positioning materials, and use-case-specific pitch decks aligned for Solutions - Own the knowledge transfer, ensuring clean, formal handoff to the expansion team - Maintain living account documentation during the pre-sales phase WHO YOU ARE - 8-12 years of experience in sales engineering, solutions consulting, product management, technical growth, chief of staff, or a similar role at the intersection of business and technology, with deep, direct experience in healthcare (payer operations, provider workflows, or health tech). You understand how a prior authorization gets processed, why claims adjudication breaks, and what a medical director actually cares about - Technical undergraduate degree (CS, engineering, math, or similar) — you don’t just understand technical concepts, you build with them. You can write code to prototype a workflow, interrogate a dataset in Python/SQL, and speak fluently with engineers about system design and API architecture - Hands-on experience designing and building GenAI solutions — not just scoping them. You’ve gotten your hands dirty with LLM pipelines, prompt engineering, RAG architectures, or similar, and can prototype on a platform like Distillery without waiting for engineering to hand you a demo - Ability to translate complex AI technical capabilities into specific, high-value business outcomes. You can make enterprise executives see why AI adoption matters now - Strong engineering-adjacent data skills: Write SQL, work in Python/pandas, and navigate messy enterprise datasets to pull the insights that drive deal narratives. Bonus if you’ve worked with healthcare-specific data formats - Exceptional communication and storytelling skills: You can command a room, structure a pitch, build a narrative arc, and make complex AI concepts land with senior executives - Deep domain expertise in healthcare operations — you’ve lived in the workflows (UM, care management, claims, network) and understand the regulatory, clinical, and operational constraints that shape AI adoption in this space. Experience navigating NCQA, CMS guidelines, or clinical documentation requirements is a strong signal. - Thrive in Ambiguity: Ability to identify critical problems in complex situations and define outcomes. - High ownership and intensity — you operate like a founder, not a task-taker - Comfortable engaging with VP/C-level executives at Fortune 500 healthcare organizations - You’ll develop deep fluency in Distyl’s Distillery platform, its primitives, and its capabilities — building demos and POCs directly on the platform, not just presenting what someone else built - Travel: Ability to travel 50% WHAT WE OFFER - The base salary range for this role is $150K – $250K , depending on experience, location, and level. In addition to base compensation, meaningful equity, along with a comprehensive benefits package - 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible time off - Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources - Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot - Complimentary in-office lunches and snacks provided - Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems - Ownership of high-impact projects across top enterprises - A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office. #LI-Hybrid We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.
AI Engineer
ABOUT DISTYL AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. WHAT WE’RE LOOKING FOR We’re opening an office in London, UK and looking for AI Engineers to design and deploy production-grade AI systems powered by LLMs. At Distyl, AI Engineers work directly with Fortune 500 companies to transform complex workflows using cutting-edge AI. You’ll build and ship real-world AI applications — from intelligent agents to full-stack AI products — and see them operate at scale in mission-critical environments. This role is highly hands-on. You’ll collaborate closely with customers, define system architectures, and build reliable, high-impact AI systems from prototype to production. Engineers at Distyl also help shape technical direction across major customer engagements, guiding enterprise teams through AI adoption and deployment. KEY RESPONSIBILITIES - Build Production AI Systems: Design, develop, and deploy robust AI applications using LLMs, including prompt engineering, agent workflows, tool use, and full-stack AI products - Work Directly with Customers: Partner closely with enterprise stakeholders to understand complex problems and translate them into impactful AI solutions - Lead System Architecture: Design scalable architectures for production AI systems, balancing performance, reliability, cost, and maintainability - Develop Our Internal Platform: Contribute to Distillery, our internal LLM application platform, by building reusable infrastructure, tools, and workflows used across customer deployments - Evaluate AI Systems Rigorously: Develop evaluation frameworks that measure model performance across accuracy, latency, cost, reliability, and safety - Ship Production-Grade Systems: Ensure systems meet high standards for observability, reliability, security, and maintainability - Raise the Engineering Bar: Improve development workflows, evaluation practices, and deployment strategies as our AI platform continues to evolve WHO YOU ARE - 3+ years of professional software engineering experience - Strong proficiency in Python or TypeScript - Experience building and deploying LLM-powered applications or AI agents in production - Experience with modern LLM tooling such as LangChain, LlamaIndex, Guardrails, MCP, or agent frameworks - Experience implementing RAG pipelines, tool use, or multi-step AI workflows - Strong understanding of AI system evaluation, debugging, and observability - Experience building reliable production systems with modern DevOps practices - Experience deploying AI systems in enterprise environments is a plus - Experience working across cloud platforms (AWS, GCP, or Azure) is a plus - Experience with agent architectures and long-horizon task execution is a plus - Familiarity with responsible AI practices, including auditability and governance is a plus WHAT WE OFFER - Competitive salary, meaningful equity, and a comprehensive benefits package - Workplace Pension Scheme with employer contributions - Private Medical Insurance (PMI) offered - Flexible Time Off + Holidays - Lunch provided on office days - Access to state-of-the-art models, generous usage of modern AI tools, and real-world business problems - Ownership of high-impact projects across top enterprises - A mission-driven, fast-moving culture that prizes curiosity, pragmatism, and excellence #LI-Hybrid We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.
Systems Architect AI/ML Infrastructure
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. THE OPPORTUNITY Deepgram's infrastructure spans bare metal GPU clusters, multi-cloud deployments, and global edge presence -- all serving real-time voice AI at massive scale while simultaneously powering large-scale model training. As a Systems Architect, you will own the end-to-end infrastructure architecture that makes this possible. You will design the compute, storage, and networking systems that serve both production inference and research training workloads, build multi-cloud strategies that balance performance with cost, and create burstable infrastructure that scales with Deepgram's rapidly growing demands. This is a senior technical leadership role where your architectural decisions shape the foundation everything at Deepgram runs on. WHAT YOU'LL DO - Define and drive the end-to-end infrastructure architecture for Deepgram's AI/ML workloads across production inference and research training - Design multi-cloud and hybrid infrastructure strategies that balance performance, reliability, cost, and vendor flexibility - Architect compute orchestration systems that efficiently schedule and manage GPU and CPU workloads across heterogeneous infrastructure - Design storage architectures that handle the massive datasets required for speech and audio ML -- from high-throughput training data pipelines to low-latency model serving - Lead capacity planning across all infrastructure dimensions, modeling growth and ensuring Deepgram can scale ahead of demand - Drive cost optimization and FinOps practices, identifying opportunities to reduce infrastructure spend without compromising performance or reliability - Design burstable, elastic training infrastructure that can scale up for large training runs and scale down to minimize idle cost - Architect research compute infrastructure that gives ML teams the resources they need while maintaining operational efficiency - Establish architectural standards, design review processes, and technical documentation practices for infrastructure decisions - Collaborate with engineering leadership to align infrastructure strategy with product roadmap and business objectives - Evaluate emerging hardware, cloud services, and infrastructure technologies for potential adoption YOU'LL LOVE THIS ROLE IF YOU - Think in systems -- you naturally see the connections between compute, storage, network, and how they interact under load - Are motivated by designing infrastructure that operates at the intersection of real-time production systems and large-scale ML training - Enjoy making architectural trade-offs where cost, performance, reliability, and velocity are all in tension - Want to work across the full infrastructure stack -- from bare metal and GPUs to cloud services and container orchestration - Are excited about building cost-effective, burstable infrastructure that enables world-class AI research - Like operating at a strategic level while staying technically deep enough to validate designs and debug complex issues IT'S IMPORTANT TO US THAT YOU HAVE - 7+ years of experience in infrastructure engineering, systems architecture, or a senior technical role focused on large-scale infrastructure - Proven experience designing multi-cloud architectures spanning AWS and at least one other major cloud provider or on-premises environment - Deep expertise in storage system design -- block, object, and file storage, including performance tuning for large-scale data workloads - Strong experience with compute orchestration using Kubernetes, and an understanding of how to schedule diverse workloads efficiently - Hands-on experience with GPU infrastructure -- procurement considerations, cluster design, driver and runtime management - Track record of capacity planning and infrastructure scaling for high-growth environments - Ability to communicate complex architectural decisions clearly to both technical and non-technical stakeholders - Strong understanding of networking fundamentals as they relate to infrastructure architecture (see our Network Engineer role for the deep specialist) IT WOULD BE GREAT IF YOU HAD - Direct experience architecting infrastructure for ML training workloads -- distributed training, large dataset management, experiment infrastructure - Background in cost optimization and FinOps practices for large-scale cloud and bare metal infrastructure - Experience operating and managing bare metal infrastructure in colocation facilities - Expertise in network architecture design, including high-bandwidth GPU interconnects and global traffic routing - Experience with infrastructure modeling and simulation for capacity planning - Familiarity with Slurm, Ray, or other HPC/ML job scheduling systems - Understanding of power, cooling, and physical infrastructure considerations for GPU-dense deployments Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Senior Data Scientist, Audio
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. Deepgram is looking for a Data Scientist to sit at the intersection between research and data: people who think deeply about what conversational data is actually composed of, what makes data valuable, and how to best leverage that. Conversational audio presents incredibly rich scientific, engineering, and infrastructure challenges that are orders of magnitude harder than working with text. Speech carries speakers, accents, dialects, emotion, overlapping talk, code-switching, domain vocabulary, and acoustic conditions that range from a quiet studio to a drive-through — all with rich context that moves the conversation. In this role you'll collaborate closely with our research, engineering, and data teams to answer those questions rigorously and at scale. You'll care deeply about what makes conversational data difficult, you'll characterize it, and you'll shape the strategies that turn it into model gains. This role rewards conviction, creativity in approach, and a real appetite for overturning your own assumptions when the data says otherwise. This is a hands-on, high-leverage role with unusual latitude to define an area from first principles. It reports to the VP of Data Operations. We're looking for people who: - See "we've always done it this way" as a starting position to argue with, not a constraint to work around - Can find the one experiment that settles a question in days rather than months - Are creative about where signal hides — in metadata, in model confidence, in the failures - Have the vision to take a scrappy proof-of-concept and scale it 100x - Are obsessed with using AI to automate and amplify their own impact WHAT YOU'LL OWN - Understand and characterize our data. Build the analysis that tells us what we actually have — languages, conditions, domains, speakers, quality — and what's underrepresented. - Design and build active-learning loops. Decide what's worth working on next based on where it will move performance, and make that decision systematic rather than intuitive. - Think deeply about how to best leverage humans in the loop. Human attention is the scarcest input in this system. Design the workflows, tooling, and model-assisted steps that make it count. - Make representative benchmarking possible. Build the curated datasets and methodology that let us make honest claims about model quality across the full diversity of real-world speech.Senior - Change our minds about what data strategies actually work. Run the experiments that separate what works from what everyone assumes works. - Care about data consistency, cleanliness, and organization — and about making data legible and accessible to non-technical teams, not just to the people who built the pipelines. - Bring method and automation to model adaptation. Turn one-off, domain- and customer-specific model work into repeatable, documented pipelines. WHAT WE'RE LOOKING FOR - Hands-on work on real data pipelines and model-facing problems in data science, ML, or applied research - Strong Python and data tooling; comfort building analysis, scoring, and automation yourself - Experience with data characterization, data selection, active learning, or similar "what should we work on next" problems - Working familiarity with speech/audio or NLP models — you can reason about model output quality, confidence, and error modes - A track record of turning ambiguous, messy data situations into measurable model or product improvements - You build systems others run without you in the room — a reusable harness, not a one-off notebook - Strong communication skills, especially translating complex findings for audiences who don't share your background - An active AI-tool user. Not aspirational — tell us what you use and what you've built with it It would be great if you also had: - Direct experience with ASR/TTS, audio data, or multilingual/code-switched data. - Experience with ensemble labeling, pseudo-labeling, or LLM-assisted annotation. - Familiarity with data provenance, PII/GDPR-aware pipelines, or model-improvement compliance. - Experience building custom or fine-tuned models for specific customers or domains. - Comfort working directly with research and engineering teams on shared infrastructure. Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $215M in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you! Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate. We are happy to provide accommodations for applicants who need them. Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Sr Data Scientist
Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack - empowering organizations to run AI across multi-vendor environments with centralized governance. The world’s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog , LinkedIn , X , and YouTube . The role of a Data Scientist at Dataiku is unique. Our Data Scientists develop solutions to real-world problems and participate in client-facing endeavours throughout the customer journey. This includes supporting their discovery of the platform, helping integrate Dataiku with other tools and technologies, providing user training, and co-developing data science projects from design to deployment. Just as non-technical skills are important, so are technical skills. Our Data Scientists work on the Dataiku platform daily. Aside from the visual tools, our team mostly uses Python, with occasional work in other languages (e.g., R, SQL, PySpark, JavaScript). An ideal candidate is excited to teach customers data science, how to use the Dataiku platform, and learn about new technologies. How you'll make an impact - Help users discover and master the Dataiku platform via user training, office hours, demos, and ongoing consultative support. - Analyse and investigate various data and machine learning applications across industries and use cases. - Provide strategic input to the customer and account teams to help our customers succeed. - Scope and co-develop production-level data science projects with our customers. - Mentor and help educate data scientists and other customer team members to aid in career development and growth. What you'll need to be successful - Curiosity and a desire to learn new technical skills - Empathy and an eagerness to share your knowledge with your colleagues, Dataiku’s customers, and the general public - Ability to clearly explain complex topics to technical as well as non-technical audiences - Over 5 years of experience with coding (Python, R, SQL) - Over 5 years of experience building ML models - Understanding underlying data systems and platform mechanics, such as Cloud architectures, K8S, Spark, and SQL What will make you stand out - Experience with Consulting and/or Customer-facing Data Science roles - Experience with Data Engineering or MLOps - Experience developing WebApps in JavaScript, RShiny, or Dash - Experience building APIs - Experience using enterprise data science tools - Passion for teaching or public speaking LI-Remote Compensation and Benefits The final compensation package for this role will be determined during the interview process and is based on a variety of factors, including, but not limited to, geographic location, internal equity, education, skill set, experience and training. Eligible roles may also be entitled to receive commission or other variable compensation through Dataiku's incentive compensation program. Dataiku also offers comprehensive benefits, including stock options, medical, dental, and vision plans, flexible spending accounts, pre-tax commuter benefits, a 401k company match, paid vacations and sick leave, paid parental leave, employer paid disability coverage, and additional health and wellbeing perks and benefits. Dataiku reserves the right to amend or modify employee perks and benefits at any time. US only national base pay ranges $176,000 - $220,000 USD What are you waiting for! At Dataiku, you'll be part of a journey to shape the ever-evolving world of AI. We're not just building a product; we're crafting the future of AI. If you're ready to make a significant impact in a company that values innovation, collaboration, and your personal growth, we can't wait to welcome you to Dataiku! And if you’d like to learn even more about working here, you can visit our Dataiku LinkedIn page . Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. This applies to all policies and procedures related to recruitment and hiring, compensation, benefits, performance, promotion and termination and all other conditions and terms of employment. If you need assistance or an accommodation, please contact us at: reasonable-accommodations@dataiku.com Protect yourself from fraudulent recruitment activity Dataiku will never ask you for payment of any type during the interview or hiring process. Other than our video-conference application, Zoom, we will also never ask you to make purchases or download third-party applications during the process. If you experience something out of the ordinary or suspect fraudulent activity, please review our page on identifying and reporting fraudulent activity here.
Fullstack Software Engineer - Core
Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack - empowering organizations to run AI across multi-vendor environments with centralized governance. The world’s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog , LinkedIn , X , and YouTube . Why Engineering at Dataiku? Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here . Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github , you can also take a look at the Gallery , a public instance showcasing some example projects (note editing is very limited and will be regularly reset). Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here . How you’ll make an impact As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes: - Data Preparation : Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs. - Add new capabilities for data integration, transformation, and visualization using LLMs - Optimize workflows for large-scale datasets and improve database support - Strengthen developer tools like Jupyter notebooks and SQL workbenches - Tech stack: Java, Python, AngularJS, Angular - AI & Machine Learning : Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference. - Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models - Collaborate with research teams on innovative machine learning experiments - Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS - Data Consumption: build the experience that makes data accessible and actionable for everyone. - Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more - Create innovative interfaces that answer business questions and surface relevant insights using LLMs - Tech stack: Angular, AngularJS, Java, Python - Data Visualization : elevate our data visualization capabilities with high-performance charting tools and dashboards. - Develop new chart types and optimize visualization performance - Enhance dash boarding capabilities to deliver fast and flexible experiences - Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring - MLOps : Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration. - Build tools to automate retraining, monitoring, and deployment of ML models - Enhance collaboration features for ML stakeholders - Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker - Platform : Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines. - Optimize processing engines for scalability and latency - Expand capabilities to support new databases and cloud platforms - Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP - AI Governance : Build features for AI compliance, connecting disparate systems and simplifying governance processes. - Develop customizable platforms for managing AI compliance and governance - Simplify policy enforcement and integration across disparate systems - Tech stack: Java, Angular, PostgreSQL What you need to be successful - We’re stack agnostic, so all you need is a significant experience in software engineering, building a real product - We’re hiring at all levels (junior, mid, senior) - A passion for combining backend performance with exceptional frontend user experience. - You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale What does the hiring process look like? - Initial call with a member of our Technical Recruiting team (45min) - Video call with an Engineering Team Lead (1h30) - Technical Assessment to show your skills (Home Test or Live Coding) - Final Interviews with our VPs of Engineering (2h) #LI-Remote What are you waiting for! At Dataiku, you'll be part of a journey to shape the ever-evolving world of AI. We're not just building a product; we're crafting the future of AI. If you're ready to make a significant impact in a company that values innovation, collaboration, and your personal growth, we can't wait to welcome you to Dataiku! And if you’d like to learn even more about working here, you can visit our Dataiku LinkedIn page . Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. This applies to all policies and procedures related to recruitment and hiring, compensation, benefits, performance, promotion and termination and all other conditions and terms of employment. If you need assistance or an accommodation, please contact us at: reasonable-accommodations@dataiku.com Protect yourself from fraudulent recruitment activity Dataiku will never ask you for payment of any type during the interview or hiring process. Other than our video-conference application, Zoom, we will also never ask you to make purchases or download third-party applications during the process. If you experience something out of the ordinary or suspect fraudulent activity, please review our page on identifying and reporting fraudulent activity here.
Staff Product Designer, Agentic Coding
RDQ427R613 About Databricks Databricks is the Data and AI company. More than 10,000 organizations worldwide rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. As agents move from demos to real production work, Databricks is building the platform that lets enterprises create, govern, and collaborate with coding agents safely and at scale. Team & Product Omnigent is Databricks' platform for building, composing, governing, and sharing AI coding agents. It lets people create and coordinate agents across different model providers and execution environments - from the CLI and IDE to desktop, mobile, and managed enterprise surfaces. Users can watch agents work live, jump in to co-drive or fork a session, and package and share reusable agents. This is a rare chance to define and refine interaction patterns at enterprise scale: how people supervise fleets of agents, intervene at the right moment, understand risk, and build trust in autonomous work - starting with coding, review, and exploration workflows. The hard design problem isn't just showing what agents are doing; it's helping people know when to trust, when to step in, and how to recover when work goes off track - across a high-density desktop workspace and lightweight mobile moments. You'll design for two audiences at once: an open-source community shaping the future of agent workflows, and enterprise teams adopting agents in governed production. Role You'll be the IC design lead for how humans and fleets of agents work together on Omnigent - leading through product strategy, systems thinking, craft, and cross-functional collaboration. You're equally comfortable shipping small design changes directly in the codebase and prototyping your way through big, ambiguous problems that don't have a spec yet. You'll own the design direction across desktop and mobile, partner deeply with engineering and product, and translate the frontier of what agents can do into experiences that feel clear, controllable, trustworthy, and surprisingly effortless. What you'll do - Own the desktop and mobile experience for live agent sessions end to end - from strategy and interaction models to visual polish and shipped detail. Shape the high-density orchestration workflows on desktop and the lightweight monitoring, review, approval, and intervention moments on mobile. - Design directly in the codebase for well-scoped changes, working alongside engineers to ship real improvements rather than handing off static mocks. - Use prototypes as a primary thinking tool. For large, vague problems, build interactive prototypes to explore, de-risk, and align the team on a direction. - Invent the interaction language for agentic work: real-time multi-agent sessions, watch/co-drive/fork flows, human-in-the-loop approvals, agent status and transparency, error and recovery states, and trust. - Define durable UX principles and interaction frameworks for agent collaboration, approvals, observability, and recovery that other teams reuse across Omnigent surfaces. - Drive cross-platform consistency with a strong, scalable design system spanning desktop and mobile. - Ground decisions in evidence - use research instincts and real usage to pressure-test ideas and know what to build next. What we're looking for - A builder-designer who works fluently with AI tools. You can make small design changes directly in a codebase, and you use prototypes - and the agents themselves - to explore larger, ambiguous problems. You regularly use AI tools in your own design and build workflow. - A portfolio of strong end-to-end craft - interaction design, visual/UI polish, and design-systems thinking - ideally on developer tools, AI/ML products, enterprise software, or other products for technical users. - Staff-level scope and impact. A track record of shipping complex, high-quality developer products and leading design direction on hard problems. - Self-directed, and comfortable in ambiguity - you help shape product direction when the path isn't defined. - A strong collaborator who raises the level of high-quality critique, clear decision-making, and tight partnership with engineering and product. Nice to have - Experience designing coding tools, IDEs, agent frameworks, or developer platforms. - Familiarity with multi-agent systems, LLM harnesses, or governance/observability tooling. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Zone 1 Pay Range $166,600 - $229,150 USD Zone 2 Pay Range $158,300 - $217,700 USD Zone 3 Pay Range $128,400 - $179,700 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Sr. Manager, AI Forward Deployed Engineering (AI F...
Sr. Manager, AI Forward Deployed Engineering (AI FDE) FEQ227R363 Mission The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements that help customers build and productionize first-of-its-kind GenAI applications, and we work cross-functionally with AI Product, Research, and Engineering to shape long-term strategic priorities. We are looking for a world-class leader to lead and grow our AI FDE team. In this role, you will lead customers on their AI transformation with Databricks, push the boundaries of our product, recruit and develop top data scientists/machine learning engineers, and manage a portfolio of key accounts. Candidates should expect to travel at least once a month. While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. The impact you will have: - Lead and scale a high-performing AI forward deployed engineering team, including hiring, mentoring, and building a team structure to support long-term growth and execution at scale - Shape cross-functional collaboration by influencing Product, R&D, and GTM, ensuring voice-of-customer insights and delivery learnings help inform the product roadmap and GTM strategy - Develop and expand executive relationships with key customers and partners (including VP+, CIO/CDO-level stakeholders), acting as a trusted advisor during complex technical engagements and AI transformations - Partner with Field Engineering and Sales leadership to set strategy for strategic accounts and coordinate delivery across functions - Lead strategic AI initiatives, practice development, and scalable delivery processes - Own OKRs for AI-services led accounts, revenue, utilization, and public references - Represent Databricks as a thought leader in AI through conference talks, published content, etc. What we look for: - Experience building and managing high-performing teams of AI/ML scientists, engineers, and leaders - Ability to scope, sell, and deliver technical engagements in enterprise environments, including managing escalations and ensuring successful customer outcomes - Strong, current technical depth in AI/ML foundations, with the ability to contribute meaningfully in architecture reviews and the curiosity to stay current as the field evolves - Experience leading teams that have shipped production AI solutions in cloud environments (AWS, Azure, or GCP) - Proven success developing strategy with senior executive stakeholders to define program-level goals, align technical vision, and build trust throughout complex enterprise engagements - Experience driving AI transformation across enterprise customers, spanning applied AI product management, organizational change management, and stakeholder alignment - Experience working across Sales, Product, and GTM to connect AI delivery to business outcomes - Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience Preferred: - Experience in a customer-facing leadership role - Experience working with Databricks Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Local Pay Range $232,900 - $320,200 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Senior Solutions Engineer (Presales, Technical, Da...
Req ID: FEQ427R358 Location: London (or surrounding areas) The Role As a Senior Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present—combining technical depth with customer-facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage. The Impact You Will Have - Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning - Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins - Own frontline technical relationships with customer engineers, data teams, and technical leads - Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption - Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations - Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community What We Look For - 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role - Proficient in Python and SQL with demonstrated ability to debug, optimise, and write production-quality code — live coding is a required interview stage - Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP) - Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink) - Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews - Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics - Strong presentation and demo skills — you will build and present a live solution during the interview - Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience) Nice to Have: - Databricks certification or experience with the Databricks Platform - Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow - Background at a data/AI company, cloud provider, or technical consulting firm Interview Process: Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Staff Applied AI Inference Engineer
Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About the Role You will spend your time making large language models run faster, cheaper, and more reliably in production. That means owning the inference stack end to end: profiling where time and cost go, bringing modern optimization techniques into real deployments, and getting deep into the serving code when the defaults are not good enough. This is core systems and performance work on some of the most demanding models in use today. The work is applied, not academic. The optimizations you build land in real customer deployments, each with its own models, traffic patterns, latency targets, and cost constraints. So while performance is the heart of the role, you will also work directly with customer engineering teams to tailor deployments to their needs, take a workload from an early proof of concept to a fully monitored production service, and make sure the gains you engineer actually show up for the people running the workload. To set expectations clearly, this is a hands-on engineering role built around coding, profiling, and low-level optimization. It also carries a customer-facing side, along with elements of product and technical solutions work, because that is where the performance work gets proven. What You'll Be Working On: - Bring current inference techniques into production and refine them. - Design and optimize serving architectures, including prefill and decode disaggregation, request routing, and related approaches. - Work down into the serving stack, from frameworks like vLLM and SGLang to the CUDA kernels underneath, profiling and running in-depth analysis to find and fix performance problems. - Adapt and scale optimization methods across many kinds of ML models, with an emphasis on large language models. - Profile and tune deployments against clear targets for latency, throughput, and cost, and keep them dependable under real traffic. - Tailor deployments to each customer's models and constraints, partnering with their engineering teams to move a workload from an early proof of concept through to a live, well-monitored production service. - Build and support the software and product features around the inference stack in a production setting, using one or more general-purpose languages, with Python preferred given how central it is to ML work. - Experiment quickly: take fuzzy goals, shape them into clear specs and focused proofs of concept, run fast experiments to find what works, and ship well-tested results without delay. - Own delivery end to end, from the first experiment through to the optimization running in production, keeping the underlying performance goals, clear specs, and follow-through front of mind, and drafting features and product requirement documents together with other engineering and product teams. - Work through ambiguity and make sound calls on tradeoffs and tooling, steering away from complexity that is not needed. - Take real pride and ownership in your work, hold yourself accountable, and look for the same from the people around you. What You'll Bring to the Team: - A Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field. - Hands-on experience shipping code in production with one or more general-purpose languages, such as Python or C++, with a strong preference for Python. - Familiarity with methods for optimizing LLMs for high throughput / low latency inference. - Comfort with modern LLM serving frameworks such as vLLM or SGLang, and with profiling and analyzing performance down to the kernel level. - A firm grasp of how GPUs are built and how they behave. - Clear interest and hands-on experience with large language models. - A working knowledge of AI/ML pipelines and the full path of developing and deploying ML models. - Strong communication skills, particularly when explaining hard technical topics to customers and teammates. Bonus points: - A track record of making software systems run faster, especially for large language models. - Experience with CUDA or comparable technologies. - A strong command of software engineering fundamentals, with a record of building and shipping AI/ML inference systems. - Experience with Docker and Kubernetes. - Prior work building or tuning AI/ML projects, particularly in a customer-facing setting. Benefits: - Competitive compensation and equity packages - Restricted Stock Units - Paid time off, paid holidays & leave of absence programs - Comprehensive health, dental & vision insurance - Employer contributions to HSA account - Paid parental leave - Paid life insurance, short-term and long-term disability - Professional development & tuition reimbursement - Mental health & wellness support - Commuter benefits (parking & transit) - Cell phone stipend - 401(k) Retirement plan with company match up to 4% of salary - Volunteer time off - Global travel insurance & emergency assistance - Daily meals allowance - Additional perks & programs specific to location Compensation Range Compensation will be paid in the range of up to $215,000 - $260,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data. Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Senior Staff Applied AI Inference Engineer
Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About the Role You will spend your time making large language models run faster, cheaper, and more reliably in production. That means owning the inference stack end to end: profiling where time and cost go, bringing modern optimization techniques into real deployments, and getting deep into the serving code when the defaults are not good enough. This is core systems and performance work on some of the most demanding models in use today. The work is applied, not academic. The optimizations you build land in real customer deployments, each with its own models, traffic patterns, latency targets, and cost constraints. So while performance is the heart of the role, you will also work directly with customer engineering teams to tailor deployments to their needs, take a workload from an early proof of concept to a fully monitored production service, and make sure the gains you engineer actually show up for the people running the workload. To set expectations clearly, this is a hands-on engineering role built around coding, profiling, and low-level optimization. It also carries a customer-facing side, along with elements of product and technical solutions work, because that is where the performance work gets proven. What You'll Be Working On: - Bring current inference techniques into production and refine them. - Design and optimize serving architectures, including prefill and decode disaggregation, request routing, and related approaches. - Work down into the serving stack, from frameworks like vLLM and SGLang to the CUDA kernels underneath, profiling and running in-depth analysis to find and fix performance problems. - Adapt and scale optimization methods across many kinds of ML models, with an emphasis on large language models. - Profile and tune deployments against clear targets for latency, throughput, and cost, and keep them dependable under real traffic. - Tailor deployments to each customer's models and constraints, partnering with their engineering teams to move a workload from an early proof of concept through to a live, well-monitored production service. - Build and support the software and product features around the inference stack in a production setting, using one or more general-purpose languages, with Python preferred given how central it is to ML work. - Experiment quickly: take fuzzy goals, shape them into clear specs and focused proofs of concept, run fast experiments to find what works, and ship well-tested results without delay. - Own delivery end to end, from the first experiment through to the optimization running in production, keeping the underlying performance goals, clear specs, and follow-through front of mind, and drafting features and product requirement documents together with other engineering and product teams. - Work through ambiguity and make sound calls on tradeoffs and tooling, steering away from complexity that is not needed. - Take real pride and ownership in your work, hold yourself accountable, and look for the same from the people around you. What You'll Bring to the Team: - A Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field. - Hands-on experience shipping code in production with one or more general-purpose languages, such as Python or C++, with a strong preference for Python. - Familiarity with methods for optimizing LLMs for high throughput / low latency inference. - Comfort with modern LLM serving frameworks such as vLLM or SGLang, and with profiling and analyzing performance down to the kernel level. - A firm grasp of how GPUs are built and how they behave. - Clear interest and hands-on experience with large language models. - A working knowledge of AI/ML pipelines and the full path of developing and deploying ML models. - Strong communication skills, particularly when explaining hard technical topics to customers and teammates. Bonus points: - A track record of making software systems run faster, especially for large language models. - Experience with CUDA or comparable technologies. - A strong command of software engineering fundamentals, with a record of building and shipping AI/ML inference systems. - Experience with Docker and Kubernetes. - Prior work building or tuning AI/ML projects, particularly in a customer-facing setting. Benefits: - Competitive compensation and equity packages - Restricted Stock Units - Paid time off, paid holidays & leave of absence programs - Comprehensive health, dental & vision insurance - Employer contributions to HSA account - Paid parental leave - Paid life insurance, short-term and long-term disability - Professional development & tuition reimbursement - Mental health & wellness support - Commuter benefits (parking & transit) - Cell phone stipend - 401(k) Retirement plan with company match up to 4% of salary - Volunteer time off - Global travel insurance & emergency assistance - Daily meals allowance - Additional perks & programs specific to location Compensation Range Compensation will be paid in the range of up to $250,000 - $300,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data. Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Senior Manager, Engineering - AI Inference
Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About the Role: As a Senior Engineering Manager, you will lead an engineering team focused on making large language models run faster, cheaper, and more reliably in production. While managing and growing the team, you will stay deeply technical and hands-on with the inference stack end to end: profiling performance, bringing modern optimization techniques into real deployments, and diving into serving code alongside your engineers. This role balances team leadership with core systems and performance engineering on demanding models in production. The work is applied, not academic. The optimizations you build land in real customer deployments, each with its own models, traffic patterns, latency targets, and cost constraints. So while performance is the heart of the role, you will also work directly with customer engineering teams to tailor deployments to their needs, take a workload from an early proof of concept to a fully monitored production service, and make sure the gains you engineer actually show up for the people running the workload. To set expectations clearly, this is an engineering leadership role that combines people management, technical direction, and hands-on coding and profiling. It also carries a customer-facing side, along with elements of product and technical solutions leadership, ensuring performance gains deliver clear business and customer value. What You'll Be Working On: - Bring current inference techniques into production and refine them. - Design and optimize serving architectures, including prefill and decode disaggregation, request routing, and related approaches. - Work down into the serving stack, from frameworks like vLLM and SGLang to the CUDA kernels underneath, profiling and running in-depth analysis to find and fix performance problems. - Adapt and scale optimization methods across many kinds of ML models, with an emphasis on large language models. - Profile and tune deployments against clear targets for latency, throughput, and cost, and keep them dependable under real traffic. - Tailor deployments to each customer's models and constraints, partnering with their engineering teams to move a workload from an early proof of concept through to a live, well-monitored production service. - Build and support the software and product features around the inference stack in a production setting, using one or more general-purpose languages, with Python preferred given how central it is to ML work. - Experiment quickly: take fuzzy goals, shape them into clear specs and focused proofs of concept, run fast experiments to find what works, and ship well-tested results without delay. - Lead team delivery end to end, guiding projects from early experiments to production optimizations, establishing performance goals, and partnering with product and engineering leaders on technical strategy and roadmaps. - Work through ambiguity and make sound calls on tradeoffs and tooling, steering away from complexity that is not needed. - Take real pride and ownership in your work, hold yourself accountable, and look for the same from the people around you. What You'll Bring to the Team: - 2+ years of experience directly managing and leading an engineering team in a high-performance or ML-focused environment. - Strong technical, hands-on experience in software engineering, low-level optimization, or ML infrastructure, with a continued desire to stay close to code and architecture. - A Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field. - Hands-on experience shipping code in production with one or more general-purpose languages, such as Python or C++, with a strong preference for Python. - Familiarity with methods for optimizing LLMs for high throughput / low latency inference. - Comfort with modern LLM serving frameworks such as vLLM or SGLang, and with profiling and analyzing performance down to the kernel level. - A firm grasp of how GPUs are built and how they behave. - Clear interest and hands-on experience with large language models. - A working knowledge of AI/ML pipelines and the full path of developing and deploying ML models. - Strong communication skills, particularly when explaining hard technical topics to customers and teammates. Bonus Points - A track record of making software systems run faster, especially for large language models. - Experience with CUDA or comparable technologies. - A strong command of software engineering fundamentals, with a record of building and shipping AI/ML inference systems. - Experience with Docker and Kubernetes. - Prior work building or tuning AI/ML projects, particularly in a customer-facing setting. Benefits: - Competitive compensation and equity packages - Restricted Stock Units - Paid time off, paid holidays & leave of absence programs - Comprehensive health, dental & vision insurance - Employer contributions to HSA account - Paid parental leave - Paid life insurance, short-term and long-term disability - Professional development & tuition reimbursement - Mental health & wellness support - Commuter benefits (parking & transit) - Cell phone stipend - 401(k) Retirement plan with company match up to 4% of salary - Volunteer time off - Global travel insurance & emergency assistance - Daily meals allowance - Additional perks & programs specific to location Compensation Range Compensation will be paid in the range of up to $250,000 - $300,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data. Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Principal Systems Software Architect
Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. ABOUT THIS ROLE: As the Principal Systems Software Architect, you will serve as the visionary lead for Crusoe’s next-generation AI infrastructure. This is a role for an industry-recognized expert who has already "seen the movie" at hyperscale and is ready to redefine the I/O path for the age of generative AI. You aren't just building a cloud; you are designing the fluid fabric that unifies Bare-Metal-as-a-Service (BMaaS), Intelligent IaaS, and Elastic CaaS into a single, high-performance pool of intelligence. In this position, you will bridge the gap between silicon and software, advising executive leadership on critical hardware/software co-design pivots while remaining hands-on enough to lead elite R&D teams in shipping production-grade kernel and orchestration code. We are looking for a master of the I/O path who can push massive-scale training workloads to the theoretical limits of hardware. This is a full-time position. WHAT YOU’LL BE WORKING ON: - Unifying Infrastructure Pillars: - Bare-Metal-as-a-Service (BMaaS): Architect systems that deliver raw GPU throughput via zero-latency InfiniBand/RDMA fabrics for massive-scale training. - Intelligent IaaS: Design highly optimized, thin virtualization layers using KVM or custom micro-VMs to provide enterprise-grade isolation without the "virtualization tax." - Elastic CaaS: Build a high-performance container substrate (utilizing Kubernetes or Slurm) that allows AI workloads to burst and scale across heterogeneous GPU nodes. - Mastering the I/O Path: Lead the architectural design of our internal cloud fabric, drawing on experience from top-tier hyperscalers to drive the technical roadmap for SR-IOV, RDMA, and virtualized GPU scheduling. - Advanced R&D Leadership: Lead elite workstreams to prototype and productionize novel methods for managing memory, networking, and compute that don't yet exist in standard cloud distributions. - Technical Strategy & Documentation: Draft white papers and RFCs that define the next two years of Crusoe’s compute and networking stack. - High-Level Debugging: Work alongside Staff and Senior engineers to resolve complex race conditions in the I/O path and optimize kernel-level memory pinning for GPU clusters. - Industry Influence: Represent Crusoe in open-source communities and industry forums to influence the global direction of cloud-native AI infrastructure. WHAT YOU’LL BRING TO THE TEAM: - Hyperscale Provenance: 12+ years of experience designing and shipping core infrastructure at a major hyperscaler (e.g., OCI, AWS, Azure, GCP) or a specialized HPC cloud. - Deep Systems Authority: Authoritative knowledge of the Linux kernel, virtualization internals (KVM, QEMU, Firecracker), and high-performance networking (RoCE v2, InfiniBand). - Hardware-Software Co-Design: Proven ability to design software that maximizes the performance of NVIDIA/AMD GPUs and high-speed NICs. - R&D Leadership: Experience leading cross-functional teams through high-ambiguity projects and delivering production-ready, mission-critical systems. - Industry Contributions: A portfolio of significant contributions to the field, which may include patents, major open-source contributions, or published research in distributed systems. - Communication Mastery: The rare ability to explain the nuances of memory-mapped I/O to an engineer and the business value of a new fabric architecture to the Board. - Mandatory Education: A Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related analytical field (or equivalent professional experience). BONUS POINTS: - Patent Holder: Possession of patents related to network virtualization, GPU scheduling, or distributed file systems. - Open Source Leadership: Maintainer status or significant contributions to the Linux Kernel, Kubernetes, or specialized HPC projects. - AI/ML Workload Expertise: Direct experience optimizing infrastructure for Large Language Model (LLM) training and inference at scale. - Peer-reviewed publications at top systems venues (OSDI, SOSP, NSDI, SC), patents, IETF RFCs - Significant open-source contributions, or industry white papers on distributed systems, high-performance networking, or AI infrastructure BENEFITS - Competitive compensation - Restricted Stock Units - Paid time off & paid holidays - Comprehensive health, dental & vision insurance - Employer contributions to HSA account - Paid parental leave - Paid life insurance, short-term and long-term disability - Professional development & tuition reimbursement - Mental health & wellness support - Commuter benefits (parking & transit) - Cell phone stipend - 401(k) Retirement plan with company match up to 4% of salary - Volunteer time off COMPENSATION RANGE $260,000 - $340,000 + Significant Equity & Bonus. Compensation is determined by the applicant's depth of expertise, previous impact at scale, and alignment with our architectural goals. Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Solutions Engineer, AI Agent
Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day. Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu , founded and led Google's Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences. Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta. About the role: As a Principal Solutions Engineer, AI Agent you will serve as the dedicated expert on AI Agent technology, a specialist resource who engages early in the sales cycle to drive and support AI Agent opportunities alongside our Core Solutions Engineering team. You bring expertise that Core SEs can pull in at the right moments, owning the AI Agent technical narrative end-to-end: from workshop facilitation and use case design through high-stakes demos and API discovery. You are a force multiplier who makes every AI Agent opportunity stronger. Responsibilities: - Be the AI Agent expert . Serve as the go-to internal and external expert on Cresta's AI Agent capabilities, engaging early in the sales process to establish technical credibility and accelerate opportunity velocity. - Work hand-in-hand with Core SEs. Partner closely with Core SEs as the AI Agent specialist, owning the AI Agent technical narrative. - Lead AI Agent workshops. Design and facilitate technical discovery workshops with prospective customers to explore AI Agent use cases, define implementation scope, and align on a path to value, translating business problems into agent-powered solutions. - Own use case and API discovery. Lead deep-dive technical discovery sessions to surface, propose, and refine AI Agent use cases. Evaluate integration requirements and API feasibility to give the deal a solid technical foundation. - Support high-stakes AI Agent demos. You step in to own the most complex and high-stakes AI Agent demonstrations in partnership with the Core SE team. - Engage early as a specialist resource. Enter opportunities early, helping to qualify and shape AI Agent deals before proof-of-value, bringing depth and structure to the technical conversation from the start. - Build the business case. Partner with Sales Directors and Core SEs to translate AI Agent solutions into financial ROI models, contributing to ROI workshops and framing the business case in terms that resonate with economic buyers. - Partner with FDX. Collaborate closely with Forward Deployed PMs and Engineers in both directions, ensuring smooth handoff from pre-sale to deployment and pulling FDX learnings on agent performance, edge cases, and customer outcomes back into pre-sale positioning and discovery. - Close the product feedback loop. Synthesize patterns from AI Agent opportunities and provide structured feedback to Product and Engineering, accelerating Cresta's roadmap to stay ahead of enterprise demand. - Elevate the SE team's AI Agent fluency. Share expertise across the broader SE organization through enablement, playbooks, and informal coaching, raising the team's collective capability. Qualifications We Value: - 5+ years in a customer-facing technical role, with at least 3–5 years in pre-sales selling to large enterprises - Hands-on experience designing, building, or selling AI Agents or agentic AI systems, including familiarity with agent frameworks, orchestration patterns, and LLM-based architectures - Practical understanding of APIs, integration patterns, and how enterprise systems connect to AI Agent workflows - Experience with Conversational AI, contact center platforms, or voice/chat automation technologies - Demonstrated ability to make complex AI concepts accessible, translating technical depth into clear business value for both technical and non-technical stakeholders - Natural workshop facilitator and collaborator, equally comfortable whiteboarding with a prospect's engineering team and presenting to a C-suite audience - Highly organized, meticulous in preparation, and relentlessly focused on delivering excellent prospect experiences - Resourceful problem-solver who can navigate ambiguity, rally internal support, and drive complex technical conversations to a clear outcome - Ability to write Python for prototyping, scripting, or demo customization is a plus - Familiarity with Salesforce.com and enterprise contact center technologies is a plus - You embody our core values Bonus points: - 2+ years of AI sales engineering experience - Experience in a high-growth startup environment Perks & Benefits: We offer a comprehensive and people-first benefits package to support you at work and in life: - Comprehensive medical, dental, and vision coverage with plans to fit you and your family - Flexible PTO to take the time you need, when you need it - Paid parental leave for all new parents welcoming a new child - Retirement savings plan to help you plan for the future - Remote work setup budget to help you create a productive home office - Monthly wellness and communication stipend to keep you connected and balanced - In-office meal program and commuter benefits provided for onsite employees Compensation at Cresta Cresta’s approach to compensation is simple: recognize impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table. The posted base salary range represents what we expect to pay for this role in a given location. Final offers are shaped by factors like experience, skills, education, and geography. In addition to base pay, total compensation includes equity and a comprehensive benefits package for you and your family. This role is variable target compensation eligible. There is potential to exceed target earnings when goals are surpassed. OTE Range: $220,000-$275,000 - variable & Offers Equity Our use of AI in recruiting: We may use AI tools in our recruiting process, which require human review and oversight. If you have questions about our use of AI or wish to opt out, please contact recruiting@cresta.ai (if you are opting out, please use the subject ‘Opt-Out’ in your email). Recording & AI transcription: We do not authorize candidates to record or use AI transcription of any interview by phone, notetaker app, AI glasses, or other device. Candidates may request an exception or accommodation for review during the interview process as needed. Recruiting impersonation scams: We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta .ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.
Senior Software Engineer, Backend (AI Agent Runtim...
Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day. Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu , founded and led Google's Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences. Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta. About the role - Build real-time AI agent infrastructure : Design and operate the stateful, low-latency runtime that powers voice and chat AI agents — from LLM streaming and conversation state management to graceful recovery and multi-channel support. - Solve distributed systems problems : Own session management across scaled-out workers — including affinity, checkpointing, crash recovery, and consistency under concurrent access. - Build a function execution platform : Own a serverless-style runtime where customers deploy custom logic — build orchestration, container lifecycle, autoscaling, and versioned rollouts. - Own developer experience and test infrastructure : Build CLI tools, local development environments, and test execution frameworks that let engineers iterate quickly and ship with confidence. - Raise the bar on production quality : Drive observability, incident response, and engineering best practices across the team. What we’re looking for - 5+ years of software engineering experience, with meaningful time spent on infrastructure, platform, or systems work. - Strong Python and Go — both are core to this role, not one primary and one secondary. - Deep understanding of distributed systems : consistency, fault tolerance, state management, concurrency. - Experience with Kubernetes and cloud-native infrastructure. - Experience building developer-facing tooling — CLIs, SDKs, local dev environments, or internal platforms. - Strong communicator who can drive technical decisions, write clear design docs, and mentor others. - High bar for code quality — thorough testing, thoughtful code review, and sustainable engineering practices. - Comfort operating what you build — on-call, incident response, and production ownership. - AI-native workflow — you actively use LLMs and AI-assisted tools in your daily development, and can leverage them to move faster and tackle problems that would otherwise be impractical. Nice-to-haves - Experience with real-time voice or streaming media systems. - Hands-on with LLM integration — streaming inference, prompt orchestration, retrieval-augmented generation. - Experience building serverless or function-as-a-service platforms. - Workflow engines (Temporal, Argo, Airflow) for durable, long-running processes. - Experience in conversational AI or speech domains. - Infrastructure-as-code and GitOps workflows. Perks & Benefits: - We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family’s needs - Paid parental leave to support you and your family - Monthly Health & Wellness allowance - Work from home office stipend to help you succeed in a remote environment - Lunch reimbursement for in-office employees - PTO: 3 weeks in Canada Compensation for this position includes a base salary, equity, and a variety of benefits. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. We are actively hiring for this role in the US and Canada. Your recruiter can provide further details. Our use of AI in recruiting: We may use AI tools in our recruiting process, which require human review and oversight. If you have questions about our use of AI or wish to opt out, please contact recruiting@cresta.ai (if you are opting out, please use the subject ‘Opt-Out’ in your email). Recording & AI transcription: We do not authorize candidates to record or use AI transcription of any interview by phone, notetaker app, AI glasses, or other device. Candidates may request an exception or accommodation for review during the interview process as needed. Recruiting impersonation scams: We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta .ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.
Senior Software Engineer, Backend (AI Agent Integr...
Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day. Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu , founded and led Google's Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences. Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta. About the role: Cresta’s AI Agent team is building enterprise-grade AI Agents that can operate inside real-world contact center environments. A critical part of that mission is enabling our AI Agents to seamlessly integrate with customers’ CCaaS platforms (Contact Center as a Service), including voice and digital channels — and to smoothly transition conversations between AI and human agents when needed. This role is focused on building the backend systems that allow our AI Agents to: - Integrate deeply with leading CCaaS platforms - Participate in live customer conversations across voice and chat - Maintain full conversation state and context - Perform real-time actions within the CCaaS ecosystem - Seamlessly hand off conversations to human agents — without losing context, history, or workflow state - Support human agents with AI assistance after transfer We are looking for strong backend engineers who want to work at the intersection of distributed systems, real-time communication, enterprise integrations, and AI Agent orchestration. This is not a pure research role — it is about building production-grade infrastructure that enables AI Agents to operate reliably in mission-critical customer environments. Why This Role Is Unique: - AI + Real-Time Systems : Work on infrastructure that enables AI Agents to participate in live conversations at scale. - Enterprise-Grade Integrations : Design robust integrations with major CCaaS platforms and customer systems. - Human-AI Collaboration : Build the systems that make AI-to-human handoff seamless, contextual, and reliable. - High-Impact Engineering : Your work directly determines how smoothly AI Agents operate in production environments. If you’re a strong backend engineer who wants to apply your expertise to real-world AI systems operating inside complex enterprise ecosystems, this role offers that opportunity. Responsibilities : - Design and build scalable backend services that integrate Cresta’s AI Agents with customers’ CCaaS platforms. - Architect systems that manage real-time conversation state, context propagation, and session lifecycle. - Implement seamless AI-to-human handoff mechanisms, ensuring full context transfer and minimal disruption to the customer experience. - Develop secure and reliable integrations with CCaaS APIs (voice, chat, messaging, routing, agent desktop, etc.). - Collaborate closely with ML engineers and AI researchers to operationalize AI Agent capabilities in live environments. - Ensure high availability, low latency, and strong observability for real-time conversation systems. - Implement authentication, authorization, compliance, and enterprise security best practices across integrations. - Drive improvements in reliability, performance, and scalability in production environments handling high interaction volumes Qualifications We Value: - Bachelor’s degree in Computer Science or related field. - 5+ years of experience building scalable backend systems in production environments. - Strong experience designing and maintaining robust APIs (REST, gRPC). - Solid understanding of distributed systems and real-time communication architectures. - Experience integrating with third-party enterprise platforms and APIs. - Experience working with CCaaS platforms or contact center systems is a strong plus. - Familiarity with AI Agents, Virtual Agents, or LLM-based systems is a plus. - Experience with containerized environments (Kubernetes, Docker). - Experience with cloud platforms such as AWS, GCP, or Azure. - Strong understanding of system reliability, observability, and security in enterprise environments. Perks & Benefits: - We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family’s needs - Paid parental leave to support you and your family - Monthly Health & Wellness allowance - Work from home office stipend to help you succeed in a remote environment - Lunch reimbursement for in-office employees - PTO: 3 weeks in Canada Compensation for this position includes a base salary, equity, and a variety of benefits. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. We are actively hiring for this role in the US and Canada. Your recruiter can provide further details. Our use of AI in recruiting: We may use AI tools in our recruiting process, which require human review and oversight. If you have questions about our use of AI or wish to opt out, please contact recruiting@cresta.ai (if you are opting out, please use the subject ‘Opt-Out’ in your email). Recording & AI transcription: We do not authorize candidates to record or use AI transcription of any interview by phone, notetaker app, AI glasses, or other device. Candidates may request an exception or accommodation for review during the interview process as needed. Recruiting impersonation scams: We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta .ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.
Technical Program Manager - Cluster Orchestration...
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com . What You’ll Do: CoreWeave is seeking a Technical Program Manager to lead complex, cross-functional programs across Cluster Orchestration and Applied Training within our AI/ML Platform Services organization. Cluster Orchestration is the platform layer that makes sure large AI workloads are scheduled, launched, and managed reliably across CoreWeave’s clusters. Applied Training is the layer on top of that infrastructure that helps researchers and customers use it for pre-training, fine-tuning, reinforcement learning, evaluations, and sandboxed experimentation. About the role: In this role, you will partner with engineering, product, infrastructure, and research-adjacent teams to improve both how workloads run on the cluster and how users interact with the training platform built on top of it. That includes driving programs across orchestration systems such as Slurm-on-Kubernetes (SUNK), Kueue, and workflow integrations, while also helping scale the environments, tooling, and operational mechanisms that make training and evaluation workflows easier to use. This is a highly cross-functional role for a TPM who combines strong technical depth, excellent execution instincts, and the ability to bring structure and clarity to fast-moving infrastructure and AI platform initiatives. Responsibilities: - Drive end-to-end program execution for cluster orchestration initiatives spanning workload scheduling, self-service provisioning, upgrade and migration flows, and platform integrations. - Lead cross-functional programs that improve how AI training, evaluation, RL, and mixed workloads run across CoreWeave clusters. - Partner with engineering and product leaders to define roadmap priorities and deliver measurable improvements in utilization, reliability, scalability, observability, and user experience. - Drive delivery for applied training initiatives across pre-training, fine-tuning, reinforcement learning, sandbox environments, and evaluation systems. - Coordinate dependencies across platform engineering, infrastructure, product, customer-facing teams, and ecosystem partners to ensure successful launches and clear operational ownership. - Build program mechanisms for release readiness, rollout planning, risk management, stakeholder communication, and post-launch review. - Establish success metrics, dashboards, and operating cadences to improve cluster efficiency, workload startup performance, time-to-research, and adoption of new platform capabilities. - Create clarity across ambiguous technical programs by aligning stakeholders, surfacing tradeoffs early, and driving decisions to resolution. Who You Are: - Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. - 8+ years of technical program management experience in cloud infrastructure, distributed systems, or AI/ML platforms. - Experience leading large-scale cross-functional programs involving scheduling systems, cluster infrastructure, or ML platform capabilities. - Strong technical fluency in Kubernetes, Slurm or comparable schedulers, distributed systems, and AI training workflows. - Demonstrated ability to define program metrics and deliver measurable outcomes in performance, reliability, scale, or operational maturity. - Excellent communication skills, with experience influencing engineering, product, and executive stakeholders. Preferred: - Experience with orchestration and scheduling technologies such as Kubernetes, Slurm, Kueue, Ray, or similar systems. - Familiarity with modern AI training and evaluation workflows, including pre-training, supervised fine-tuning, reinforcement learning, and experiment or sandbox environments. - Understanding of GPU infrastructure, cluster capacity planning, multi-tenant execution, and distributed training tradeoffs. - Experience building launch processes, release governance, dependency management, and operational review mechanisms in fast-scaling environments. - Familiarity with AI developer and research tooling such as W&B, SkyPilot, or adjacent ecosystem platforms. Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: - Be Curious at Your Core - Act Like an Owner - Empower Employees - Deliver Best-in-Class Client Experiences - Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! The base salary range for this role is $237,000 to $261,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: - Medical, dental, and vision insurance - 100% paid for by CoreWeave - Company-paid Life Insurance - Voluntary supplemental life insurance - Short and long-term disability insurance - Flexible Spending Account - Health Savings Account - Tuition Reimbursement - Ability to Participate in Employee Stock Purchase Program (ESPP) - Mental Wellness Benefits through Spring Health - Family-Forming support provided by Carrot - Paid Parental Leave - Flexible, full-service childcare support with Kinside - 401(k) with a generous employer match - Flexible PTO - Catered lunch each day in our office and data center locations - A casual work environment - A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Staff Specialist Field Engineer, Robotics
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com . What You’ll Do The Physical AI Field Engineering team at CoreWeave deploys AI solutions within enterprise engineering organisations, helping customers realise measurable value from machine learning applications. As we build our presence in Robotics, we are seeking a Staff Specialist Field Engineer to establish and lead this vertical. You will define how the team engages with robotics customers, set the technical standard for the practice, and lead complex customer engagements from initial scoping through to embedded deployment and expansion. This role requires genuine depth on both sides of the engagement: you must be credible to the control engineers, roboticists, and ML researchers in the room, and capable of building and validating ML solutions independently using our product stack. You will work across CoreWeave’s AI platform (including Monolith, Marimo, and W&B Models) to design and deploy solutions and build customer-facing applications tailored to specific robotics use cases. A core part of this role is building and iterating on customer-facing applications using the CoreWeave product stack tailored to specific engineering use cases. These applications are the product the customer uses; you are not just deploying tools but building at the product edge. You will gather and synthesise signals from real customer deployments, identifying where customer needs are consistent enough across accounts to inform development of standalone capabilities. You will contribute to the wider Field Engineering team’s Physical AI knowledge framework and provide critical signals of what customers need in the field and what ultimately gets built in the product. Who You Are - 8+ years experience in robotics systems development, robot learning, or AI/ML for physical autonomous systems, with experience in manipulation, locomotion, or mobile robotics. - Deep understanding of physical system dynamics, kinematics, and the engineering constraints that govern real-world robot behaviour. - Hands-on ML capability: able to build, validate, and deploy ML solutions independently in Python using modern ML frameworks. - Proficient in working directly in JupyterHub, VS Code, Marimo, and W&B Models to build and deploy customer-facing applications. - Working knowledge of ML approaches relevant to robotics: imitation learning, reinforcement learning, sim-to-real transfer, anomaly detection for physical systems, or trajectory prediction. - Able to validate ML solutions on physical grounds and identify when a model output violates the constraints of the real system it represents. - Proven experience leading complex technical customer engagements, managing multi-stakeholder environments, and maintaining executive relationships. - Familiarity with robot simulation environments (Isaac Sim, MuJoCo, Gazebo, or similar) and their role in training and validating robot learning pipelines. - Able to translate field observations into structured product signals that are actionable for an engineering team. - Bachelor’s or Master’s degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, Physics, or a related technical discipline. Preferred - Experience deploying robot learning systems on real hardware, including managing the sim-to-real gap in production settings. - Familiarity with foundation models for robotics and their application to generalised manipulation or locomotion tasks. - Experience working with compute-intensive training workloads and an understanding of the infrastructure requirements they create. - Experience identifying and progressing expansion opportunities within strategic customer accounts. - Track record of contributing to internal knowledge frameworks, technical publications, or industry forums in the robotics space. - Familiarity with ROS/ROS2 and associated tooling. Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams — even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. - You understand why the same neural network that works in simulation can fail on hardware, and you find solving that problem an interesting challenge. - You want to build AI solutions that run on real robots in real environments, not in controlled demonstrations. - You are equally comfortable discussing learning algorithm design with an ML researcher and actuator dynamics with a mechanical engineer. - You want to bring your robotics domain expertise into a team that already knows how to land and expand AI solutions with engineering customers, and you see being the domain authority that opens a new vertical as a genuinely compelling opportunity. The base salary range for this role is $177,000 to $237,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: - Medical, dental, and vision insurance - 100% paid for by CoreWeave - Company-paid Life Insurance - Voluntary supplemental life insurance - Short and long-term disability insurance - Flexible Spending Account - Health Savings Account - Tuition Reimbursement - Ability to Participate in Employee Stock Purchase Program (ESPP) - Mental Wellness Benefits through Spring Health - Family-Forming support provided by Carrot - Paid Parental Leave - Flexible, full-service childcare support with Kinside - 401(k) with a generous employer match - Flexible PTO - Catered lunch each day in our office and data center locations - A casual work environment - A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Senior Product Manager, W&B Models
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com . About the Role W&B Models is the experiment tracking platform used by the world's leading AI teams, from frontier labs training foundation models to enterprise teams fine-tuning for production. Researchers live in it daily: logging runs, comparing training curves, debugging divergences, building reports, and deciding what to try next. As Senior Product Manager for Models, you'll drive improvements across the core experiment workflow: how researchers design experiments, visualize what's happening inside them, monitor long-running training jobs, and analyze results across hundreds or thousands of runs. You'll do this at a moment when autoresearch and agentic workflows are reshaping what that loop looks like. Your job is to deeply understand how modern ML research actually gets done and make the inner loop of hypothesis → run → analysis → next run dramatically faster and more insightful. That loop looks different for a frontier researcher running thousand-run sweeps and an enterprise team fine-tuning open models against domain evals and cost targets – you'll serve both. This role reports to the Director of Product Management and partners closely with engineering, design, and teams across W&B and CoreWeave. What You'll Do - Advance the researcher's daily workflow. Experiment tracking is where researchers spend their days (and nights). You'll drive the roadmap for how runs are organized, compared, and understood, with a relentless focus on the questions researchers need to answer. - Rethink how training is visualized and monitored. Modern training runs are long, expensive, and failure-prone. You'll shape how W&B surfaces what matters mid-run — loss curves, system metrics, evals, anomalies — so teams catch problems early and understand their models more deeply, across web and mobile. - Make evaluations a first-class part of experiment tracking. Evals are how teams know whether a model is actually getting better, but today they live at arm's length from the training workflow. You'll drive the roadmap for logging, comparing, and analyzing eval results within Models — across runs, across training steps, and at the row level where regressions actually hide. - Make analysis at scale a first-class experience. As experiments grow from dozens of runs to thousands, the hard problems shift from logging to sense-making. You'll define how researchers slice, aggregate, and reason across large experiment histories, including where AI-assisted analysis can do work humans currently do by hand. - Ground every decision in how researchers actually work. You'll spend real time with users, from frontier lab researchers to individual practitioners, and translate what you learn into product decisions the whole team can rally behind. - Ship with quality and speed. You'll own execution from problem definition through launch and iteration, using usage data and customer feedback to guide each stage. W&B's users are discerning; polish and performance are features. Who You Are - You've lived the ML researcher's workflow. You've trained models yourself, or worked so closely with researchers that their workflow is second nature. You know what it feels like to babysit a training run, debug a loss spike at 2am, or dig through a hundred runs to figure out which ablation mattered. - You have 3+ years of product management experience on technical products for developer or researcher audiences, with a track record of shipping products users love. - You have strong instincts for data visualization and product design. You can reason about what makes a chart, dashboard, or comparison view genuinely useful vs. merely present, and you sweat the details of how information is displayed. - You reach for AI tools instinctively. Claude, Codex, and agentic workflows are how you work: for prototyping, analysis, and exploring ideas. You're excited to build products for people who work the same way. - You're technically fluent. You can read a training script, discuss evaluation methodology, and hold your own in architecture conversations with engineers. - You communicate with clarity and precision , keeping engineering, design, and go-to-market stakeholders aligned without ceremony. Nice to Have - Hands-on experience with experiment tracking tools, with opinions of where they all (especially W&B!) fall short - Experience with enterprise ML platforms or fine-tuning services (SageMaker, Vertex, Databricks, Together, Fireworks), and views on what they get right and wrong - Public technical writing, whether a paper, a conference talk, or blog posts discussing ML topics - "AI Twitter" presence or participation. - Experience conducting user research and/or engaging in developer communities The base salary range for this role is $182,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: - Medical, dental, and vision insurance - 100% paid for by CoreWeave - Company-paid Life Insurance - Voluntary supplemental life insurance - Short and long-term disability insurance - Flexible Spending Account - Health Savings Account - Tuition Reimbursement - Ability to Participate in Employee Stock Purchase Program (ESPP) - Mental Wellness Benefits through Spring Health - Family-Forming support provided by Carrot - Paid Parental Leave - Flexible, full-service childcare support with Kinside - 401(k) with a generous employer match - Flexible PTO - Catered lunch each day in our office and data center locations - A casual work environment - A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
Principal Engineer - Perf and Benchmarking
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com . About this role We’re looking for a Principal Engineer to be the technical lead of CoreWeave’s Benchmarking & Performance team. You will be responsible for our planet-scale performance data warehouse: Ingesting, storing, transforming and analyzing performance events in all the data centers across our global infrastructure. You will also be an integral part of achieving industry-leading end-to-end performance benchmarking publications: If MLPerf (Training & Inference), Working closely with NVIDIA (Megatron-LM, TensorRT-LLM & DGX cloud) and the open-source community (llm-d, vLLM and all popular ML frameworks) speak to you, come help us demonstrate CoreWeave’s performance reliability leadership in the field. What you’ll do - Strategy & Leadership - Define the multi-year benchmarking strategy and roadmap; prioritize models/workloads (LLMs, diffusion, vision, speech) and hardware tiers. Build, lead, and mentor a high-performing team of performance engineers and data analysts. Establish governance for claims: documented methodologies, versioning, reproducibility, and audit trails. - Perf Ownership - Lead end-to-end MLPerf Inference and Training submissions: workload selection, cluster planning, runbooks, audits, and result publication. Coordinate optimization tracks with NVIDIA (CUDA, cuDNN, TensorRT/TensorRT-LLM, Triton, NCCL) to hit competitive results; drive upstream fixes where needed. - Internal Latency & Throughput Benchmarks - Design a Kubernetes-native, repeatable benchmarking service that exercises CoreWeave stacks across SUNK (Slurm on Kubernetes), Kueue, and Kubeflow pipelines. Measure and report p50/p95/p99 latency, jitter, tokens/s, time-to-first-token, cold-start/warm-start, and cost-per-token/request across models, precisions (BF16/FP8/FP4), batch sizes, and GPU types. Maintain a corpus of representative scenarios (streaming, batch, multi-tenant) and data sets; automate comparisons across software releases and hardware generations. - Tooling & Automation - Build CI/CD pipelines and K8s controllers/operators to schedule benchmarks at scale; integrate with observability stacks (Prometheus, Grafana, OpenTelemetry) and results warehouses. Implement supply-chain integrity for benchmark artifacts (SBOMs, Cosign signatures). - Cross-functional & Community - Partner with NVIDIA, key ISVs, and OSS projects (vLLM, Triton, KServe, PyTorch/DeepSpeed, ONNX Runtime) to co-develop optimizations and upstream improvements. Support Sales/SEs with authoritative numbers for RFPs and competitive evaluations; brief analysts and press with rigorous, defensible data. Who you are - 10+ years building distributed systems or HPC/cloud services, with deep expertise on large-scale ML training or similar high-performance workloads. - Proven track record of architecting or building planet-scale data systems (e.g., telemetry platforms, observability stacks, cloud data warehouses, large-scale OLAP engines). - Deep understanding of GPU performance (CUDA, NCCL, RDMA, NVLink/PCIe, memory bandwidth), model-server stacks (Triton, vLLM, TensorRT-LLM, TorchServe), and distributed training frameworks (PyTorch FSDP/DeepSpeed/Megatron-LM). - Proficient with Kubernetes and ML control planes; familiarity with SUNK, Kueue, and Kubeflow in production environments. - Excellent communicator able to interface with executives, customers, auditors, and OSS communities. Nice to have - Experience with time-series databases, log-structured merge trees (LSM), or custom storage engine development. - Experience running MLPerf submissions (Inference and/or Training) or equivalent audited benchmarks at scale. - Contributions to MLPerf, Triton, vLLM, PyTorch, KServe, or similar OSS projects. - Experience benchmarking multi-region fleets and large clusters (thousands of GPUs). - Publications/talks on ML performance, latency engineering, or large-scale benchmarking methodology. The base salary range for this role is $206,000 to $333,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: - Medical, dental, and vision insurance - 100% paid for by CoreWeave - Company-paid Life Insurance - Voluntary supplemental life insurance - Short and long-term disability insurance - Flexible Spending Account - Health Savings Account - Tuition Reimbursement - Ability to Participate in Employee Stock Purchase Program (ESPP) - Mental Wellness Benefits through Spring Health - Family-Forming support provided by Carrot - Paid Parental Leave - Flexible, full-service childcare support with Kinside - 401(k) with a generous employer match - Flexible PTO - Catered lunch each day in our office and data center locations - A casual work environment - A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
AI Engineer
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com . What You'll Do: The Field Engineering organization at CoreWeave supports the clients running some of the largest AI workloads in the world. This team builds the tooling that engineers rely on to identify and diagnose customer issues faster. We work where AI and deterministic based systems meet live production infrastructure, so what we build has to be accurate, has to show its reasoning, and has to earn the trust of engineers who are the real experts solving issues. About the Role: As an AI Engineer, you'll design, build, and operate systems that engineers use during real customer incidents. You will define the right balance between deterministic and AI systems, and work with both. For AI systems, you'll own the agent logic, the retrieval behind it, the safeguards that stop it from acting on bad information, and the measurement that tells us whether it's actually helping. This is a full-ownership role: you ship your own services and stay responsible for how they behave in production. You'll work closely with the engineers who use what you build. In this role, you will: - Design and build AI agents that investigate and act on real customer issues. - Build the safeguards that make that safe: grounding model output in authoritative data, requiring human approval before consequential actions, and defining the conditions under which the system should stop. - Build and evaluate retrieval over a large body of historical support data, measured against how experienced engineers handled the same problems. - Determine the optimal balance between AI and deterministic logic. - Instrument these systems for quality, cost, and adoption, then use what you learn to decide what to build next. - Deploy and operate your own services on Kubernetes, including supporting them when something breaks. - Partner with support engineers and domain experts, including sitting in on live investigations to see where automation helps and where it gets in the way. Who You Are: - 3+ years of professional software engineering experience, with strong proficiency in Go or Python. - Experience taking an AI application from prototype to production use and supporting it afterward. - Hands-on experience with agent patterns: tool and function calling, multi-step orchestration, and handling incorrect model output. - Experience building and evaluating retrieval systems, including measuring quality against a baseline using held-out data. - Experience designing controls for automation that acts on production systems, such as approval steps, idempotency, and audit trails. - Experience diagnosing failures in LLM applications and fixing the underlying cause rather than the symptom. - Experience with observability for LLM applications, including tracing, cost, and latency. - Working knowledge of Kubernetes and experience deploying services through CI/CD. - Experience integrating with third party APIs, including authentication and secrets handling. Preferred: - Experience building conversational or chat-based interfaces for internal users. - A background in infrastructure, SRE, or technical support, and comfort reading logs and metrics from a live system. - Experience testing both deterministic and non-deterministic systems. - Experience with fine-tuning or building training datasets from production data. - Open source contributions to AI tooling or agent frameworks. Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. - You can tell the difference between the thing that's interesting and the thing that's urgent, and you'll say so out loud when they aren't the same. - You've worked with a team that already had tooling they liked, and found the integration instead of arguing for a rewrite. - You'd rather sit in on a real incident than infer how the work goes from a ticket. - Blunt feedback from the engineers using your software is the most useful thing you'll hear all week, and you don't get defensive about it. The base salary range for this role is $143,00 to $210,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: - Medical, dental, and vision insurance - 100% paid for by CoreWeave - Company-paid Life Insurance - Voluntary supplemental life insurance - Short and long-term disability insurance - Flexible Spending Account - Health Savings Account - Tuition Reimbursement - Ability to Participate in Employee Stock Purchase Program (ESPP) - Mental Wellness Benefits through Spring Health - Family-Forming support provided by Carrot - Paid Parental Leave - Flexible, full-service childcare support with Kinside - 401(k) with a generous employer match - Flexible PTO - Catered lunch each day in our office and data center locations - A casual work environment - A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.
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