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Global Indirect Tax Manager
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. Position Overview We are seeking a Global Indirect Tax Manager to own the organization’s indirect tax function. This role will be responsible for indirect tax compliance, reporting, planning, audits, and risk management, while serving as a key advisor to Finance, Accounting, Legal, Operations, and other business stakeholders. The successful candidate will bring strong technical expertise in indirect taxation, excellent judgment, and the ability to translate complex tax requirements into practical business solutions. This role is well suited to a tax professional who can operate strategically while maintaining strong oversight of day-to-day compliance and execution. Key Responsibilities Indirect Tax Compliance and Reporting - Manage indirect tax compliance activities, including sales and use tax, VAT/GST, excise taxes, and other transaction-based taxes, as applicable. - Ensure accurate and timely preparation, review, and filing of indirect tax returns and related payments. - Maintain appropriate controls, documentation, reconciliations, and supporting workpapers for indirect tax accounts. - Monitor filing obligations, registrations, nexus requirements, and changes in the organization’s tax footprint. - Manage third-party service providers supporting indirect tax compliance and reporting. Tax Advisory & Planning - Provide clear advice to business partners on the indirect tax implications of new products, services, customer arrangements, geographic expansion, supply-chain changes, and other strategic initiatives. - Research and interpret complex indirect tax legislation, regulations, and administrative guidance. - Identify opportunities to improve tax efficiency, reduce risk, and recover overpaid taxes where appropriate. - Partner with Legal and Finance teams on contracts and commercial arrangements to ensure appropriate indirect tax treatment. Audits & Risk Management - Lead indirect tax audits, examinations, inquiries, and correspondence with tax authorities. - Develop audit strategies and coordinate responses, documentation, and negotiations with relevant authorities. - Proactively identify areas of indirect tax exposure and implement appropriate remediation plans. - Maintain and enhance the organization’s indirect tax control framework and ensure appropriate governance over key tax processes. - Monitor legislative and regulatory developments and assess their impact on the business. Systems, Technology & Process Improvement - Partner with Finance, Accounting, IT, and Operations to ensure appropriate indirect tax configuration within ERP, billing, procurement, and tax determination systems. - Drive automation and process improvements to increase the accuracy, scalability, and efficiency of indirect tax processes. - Support system implementations, upgrades, integrations, and business transformation initiatives from an indirect tax perspective. - Improve the use of data and analytics for compliance, reconciliations, audit defense, and tax risk management. Qualifications - Bachelor’s degree in Accounting, Finance, Taxation, Business, or a related field. - CPA, CA, JD, LLM, or other relevant professional qualification preferred. - 5+ years of progressive tax experience, with significant experience in indirect taxation. - Strong technical knowledge of sales and use tax and/or VAT/GST; experience with additional indirect taxes is advantageous. - Experience managing indirect tax compliance, audits, research, and advisory matters. - Experience in a Big Four/public accounting firm, multinational organization, or complex corporate tax environment preferred. - Strong understanding of accounting processes, financial systems, and internal controls. - Experience with ERP and indirect tax technology platforms such as NetSuite, Anrok ,Vertex, similar systems is preferred. - Demonstrated ability to manage multiple priorities and complex projects in a fast-paced environment. - Strong analytical, problem-solving, project-management, and communication skills. - Ability to work effectively across functions and influence stakeholders at multiple levels of an organization. Preferred Attributes - Strategic thinker with a strong understanding of how tax considerations affect broader business decisions. - Hands-on leader who is comfortable moving between technical analysis and operational execution. - Strong attention to detail while maintaining a commercial and risk-based perspective. - Ability to simplify complex tax concepts and provide clear, actionable recommendations. - Comfortable operating in an evolving environment and building scalable tax processes. - Demonstrated commitment to developing people, improving processes, and strengthening controls. Success in This Role Success will be measured by the accuracy and timeliness of indirect tax compliance, effective management of tax risks and audits, quality of advice provided to the business, improvements in processes and technology, and the ability to build a scalable indirect tax function that supports the organization’s growth. 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.
Senior Applied AI Engineer
About the role Scale's Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. As a Senior Applied AI Engineer, you'll own the AI behaviour of production systems our clients depend on, including the agents, evaluations, and backend integration behind them. You'll lead delivery for your workstream and act as the technical point of contact for clients on how their AI performs on live data. What you'll do - Own the AI layer of production systems for public sector clients, including agents, model integration, and the backend services they run on - Build production agents from established architectural patterns, with reliable tool calling, guardrails, and observability - Select and adapt established evaluation methods, and design new evaluations for client-specific risks - Apply context engineering, retrieval-augmented generation, model adaptation, or inference optimisation - Investigate regressions in the systems you own, lead root-cause analysis, and implement preventative changes - Lead project planning for your workstream and manage client expectations on scope, risk, and delivery - Codify recurring client work into reusable tooling, evaluation components, or guidance that other engineers adopt - Mentor engineers through code review, pairing, and delegated ownership What we look for - Backend engineering experience, with a track record of taking AI/ML systems into production and keeping them reliable - Ownership of the AI behaviour of a production system end to end, rather than delivering a component scoped by another team - Hands-on evaluation design that ties model behaviour to real-world outcomes, used to catch regressions - Comfort working directly with clients, including explaining model behaviour and trade-offs to non-technical stakeholders - Practical knowledge of handling regulated or sensitive data and designing for auditability; sovereign or on-premise deployment experience is valuable - Experience leading root-cause analysis on production AI or ML systems Where this role sits Your primary accountability covers production AI behaviour, its backend integration, and the evaluation required for a specific customer. Senior Full-Stack Engineers own the complete user-facing application and its infrastructure. ML Research Engineers lead novel agent architecture and the benchmark methodology used across accounts. The roles work together on agents and evaluation, with accountability set by the scope of the problem. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Data Scientist, Preparedness
About the Team The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework . Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models. The mission of the Preparedness team is to: - Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards misuse risks whose impact could be catastrophic to our society - Ensure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systems Preparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society. About the Role We’re hiring a Data Scientist to help build, evaluate, and continuously improve mitigations that prevent extreme harms from AI systems. This role is for an experienced, highly autonomous individual contributor who can take ambiguous problem statements, structure rigorous analyses, and translate findings into actionable product and policy changes. This position goes beyond “running evals.” You’ll help create mitigation intelligence and monitoring systems that enable OpenAI to detect issues early, measure effectiveness over time, and reduce both over-blocking (unnecessary friction) and under-blocking (missed harm). What You’ll Do - Evaluate and improve mitigation systems, including classifiers and detection pipelines across domains (e.g., biosecurity, cybersecurity, and emerging risk areas). - Diagnose false positives and false negatives with deep error analysis, root cause investigation, and clear recommendations for mitigation adjustments. - Build monitoring and measurement frameworks to track mitigation effectiveness over time and across user segments and use cases. - Identify trends in over-blocking vs. under-blocking, quantify customer impact, and propose prioritized interventions. - Develop insights from customer feedback, complaints, and usage patterns to detect shifts in adversarial behavior and system failure modes. - Expand risk monitoring into new areas, including cybersecurity threats and model loss-of-control or sabotage scenarios, in partnership with domain experts. - Communicate results to technical and executive stakeholders with crisp narratives, decision-ready metrics, and clear tradeoffs. You might thrive in this role if you are: - An autonomous operator: you can take a problem statement and independently structure the analysis end-to-end. - Strong at executive-ready communication: concise, clear, and outcome-oriented. - Skilled in turning analysis into productable changes: you’re comfortable influencing across functions to drive mitigation improvements. Qualifications - Significant experience in data science or applied analytics in high-stakes domains (e.g., security, trust & safety, abuse prevention, fraud, platform integrity, or reliability). - Strong foundations in experimentation, causal thinking, and/or observational inference; ability to design robust measurement under imperfect data. - Fluency in SQL and Python (or equivalent) for analysis, modeling, and building monitoring workflows. - Experience building metrics, dashboards, and operational monitoring that meaningfully changes outcomes (not just reporting). - Track record of driving cross-functional impact with engineering, product, and research partners. - Cybersecurity data science experience (strong preference), including exposure to threat modeling, adversarial dynamics, abuse patterns, or security telemetry. - Experience with classifier evaluation, calibration, thresholding, and error analysis at scale. Familiarity with detection systems in adversarial settings (e.g., evasion, distribution shift, feedback loops). - Trust & Safety experience is helpful, but not required. - Genuine interest in AI safety, alignment, and catastrophic risk prevention. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 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. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Account Executive - AI Native, EMEA
About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re hiring an Account Executive to win and grow Modal’s relationships with AI-native companies: the startups and scale-ups building their products on models from day one. These teams move fast, so our sales cycle does too. Deals often move forward from the very first call, and you’ll usually be talking directly with the founder or technical leader who owns the budget. You’ll own the full cycle, from sourcing to close to expansion, and you’ll partner closely with our founders, engineering, and product teams. You’ll also help build Modal’s presence in the developer community, because in this market, the best pipeline comes from engineers who already love the product. The ideal candidate has an engineering background, has worked as a solutions architect or in a similar technical role, and has since moved into selling. You’re as comfortable debugging a cold-start issue with an ML engineer as you are negotiating terms with a CEO. What You’ll Do: - Own a book of AI-native accounts and close new business quickly, often moving from first call to signed deal in weeks rather than quarters. - Sell directly to founders, CTOs, and heads of ML who define the ideal customer and hold the budget from day one. - Get hands-on in technical conversations: scope workloads, set up quick proofs of concept, and show customers how Modal fits into their stack. - Spot expansion early and help fast-growing customers scale their inference, training, and sandbox workloads as their usage takes off. - Help build and engage Modal’s developer community through events, meetups, open-source channels, and word of mouth. - Bring sharp, structured customer feedback to our product and engineering teams to shape the roadmap. - Help define how Modal sells to AI-native companies, including the playbooks, pricing motions, and processes we’ll scale as the team grows. Requirements: - An engineering background, followed by time as a solutions architect, sales engineer, or similar customer-facing technical role, and now experience as a closing seller. - Current or recent experience at an AI-native company, ideally selling infrastructure, ML/AI, or developer tools. - A track record of selling directly to founders and technical leaders and closing deals quickly in a high-velocity sales cycle. - Experience building or engaging a developer community, or a clear point of view on how community drives pipeline. - Enough technical depth to go deep on GPUs, inference, containers, and model training with engineers, without needing a sales engineer in the room. - Excellent communication, negotiation, and relationship-building skills. - Comfort in a fast-moving, early-stage environment and excitement about building processes from the ground up. - Ability to work in person from our office 5 days a week.
Data Annotation Specialist, Safety
Who are we? Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers. Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products. Join us on our mission and shape the future! Why this role? We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models to be exact) learn in similar ways to humans: by way of feedback. By labeling, ranking, auditing, prompting, red teaming, and correcting output, you will improve Large Language Model’s performance for iterations to come, thus having a lasting impact on Cohere’s tech. Cohere is looking for Data Annotation Specialists with backgrounds and skills in Trust & Safety, Content Moderation, AI model evaluation, or related fields. This role is best suited for candidates who bring strong contextual judgment, cultural and bias sensitivity, and experience applying nuanced guidelines to complex or ambiguous content. Successful candidates will be highly detail-oriented, comfortable evaluating safety risks across different user intents and scenarios, and able to make consistent, well-reasoned decisions with a high degree of independence after onboarding. IMPORTANT CONTEXT ON THIS ROLE : In this position, you will be asked to engage with human-generated and model-generated tasks which will sometimes mean intentional exposure to explicit content. Your annotations on these explicit tasks will be used to prevent the Large Language Model from generating unintentional, adversarial, toxic, or unsafe outputs. The types of explicit content you may be exposed to may include but are not limited to those of a sexual, violent, or psychologically disturbing nature. Please Note: This is a part-time, remote, independent contractor position available within Canada or the United States. We seek candidates who are able to commit to 16 hours per week minimum at a 45 CAD/hour or 40 USD/hour contract rate, depending on your location, consisting of 30/hour base pay plus 15 CAD or 10 USD/hour hazard pay. This role is BYOD 💻 - Bring Your Own Device (laptop). 12 months contract with potential for extension. As a Data Annotation Specialist on safety task, you will: - Evaluate and improve model safety: Label, rank, audit, and refine human- and model-generated text to improve safety, quality, and policy alignment, including content that may be sexual, violent, or psychologically disturbing. - Apply nuanced safety judgment : Assess model outputs against detailed safety guidelines, rubrics, and style standards, making consistent decisions across ambiguous, sensitive, and context-dependent cases. - Create prompts and safety test cases : Write realistic prompts, user scenarios, and adversarial examples that help evaluate model behavior across safety categories and uncover unsafe, evasive, over-refusing, or policy-inconsistent responses. - Support quality and calibration : Identify annotation inconsistencies or unclear guidelines, and provide actionable feedback on recurring edge cases, model failures, and opportunities to improve data quality. - Work with precision and independence: Complete annotation tasks with strong attention to detail, while being comfortable working independently in a globally distributed, asynchronous team environment. You may be a good fit if you have: - 1+ years of experience in Content Moderation,Trust and Safety, AI data annotation, LLM evaluation, or a related analytical role, with exposure to quality assurance, red teaming, and/or prompt engineering preferred. - Experience applying detailed guidelines to complex and sensitive content, with strong contextual and sociocultural judgment and the ability to recognize and manage personal bias. - Emotional resilience: Comfort working with content that contains unsafe, explicit, and/or toxic content, including content of a sexual, violent, or psychologically disturbing nature. - Excellent command of written English and the ability to clearly justify content evaluations, including why an output is safe, unsafe, high-quality or low-quality. Bonus points if you are fluent in another language! - Strong attention to detail and commitment to accuracy, with the ability to maintain consistency across high-volume and monotonous tasks. - Strong execution in a remote environment, including good time management, comfort using new tools, and the ability to work independently in a global, asynchronous team. The Candidate Journey: Initial Screening - Once you have submitted your application our Talent Team will review your resume and writing samples. Virtual Annotation Test - This assignment will test your written skill through various language-based tasks, such as a a writing sample, interacting with a chat bot, and more. Video Screen - If selected to move forward, you will have a short video call with a member of our Operations Team! Offer - Independent Contractor Agreement As an independent contractor, you maintain control over how you complete your work and may work with multiple clients simultaneously, although we ask you to declare if any of these are with a direct competitor of Cohere and maintain IP confidentiality of the Cohere project. Independent contractors are not eligible for health benefits or other benefits provided to employees. Compensation for services is provided to contractors by contractors invoicing for services provided pursuant to the terms of our agreement with the contractor. It is important to understand that as an independent contractor, continuous work is not guaranteed . The client-contractor relationship is fundamentally project-based, meaning engagements may be temporary, periodic, or intermittent based on our organizational needs and project availability . As an independent contractor, you should anticipate fluctuations in workflow and therefore compensation for services when Cohere does not require as many hours of services in a week. Prospective candidates, please be advised: this role involves working with human generated and model generated tasks that may involve exposure to not safe for work (NSFW) text content as part of data annotation tasks, including explicit, offensive, or other inappropriate material. If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form , and we will work together to meet your needs.
AI Deployment Strategist, Science - EMEA
About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role As an AI Deployment Strategist with Science Focus , you will drive the adoption and deployment of Mistral's AI solutions for science-heavy projects , working closely with customers from strategic vision to production implementation in domains like computer vision, robotics, and embodied AI . This role sits at the intersection of deep technical expertise , business strategy, and hands-on deployment, ensuring our customers achieve transformative outcomes in specialized AI applications . You will partner with senior executives to design AI roadmaps for science-driven use cases , collaborate with the Applied AI and Research teams to deliver solutions in production, and ensure seamless transitions from presales to postsales. Your work will directly contribute to expanding Mistral's capabilities in cutting-edge AI domains . This role is ideal for those who thrive in a fast-paced environment, enjoy solving complex technical challenges in specialized domains, and are passionate about turning AI science into real-world impact. What You Will Do Strategic Discovery & Vision Setting - Lead executive-level workshops to identify science-specific business challenges and opportunities where Mistral's AI can drive step-change improvements in vision, robotics, embodied AI, and other specialized domains . - Co-create AI adoption roadmaps with customers, articulating the "art of the possible" in science applications and a clear path to value. - Collaborate with Account Executives to develop business cases for technically complex, science-driven solutions , quantify ROI, and align with customer objectives. AI Solution Design & Deployment (Science Focus) - Architect end-to-end AI solutions for specialized domains, integrating Mistral's models and platform into science-specific workflows and technical infrastructure. - Partner with the Applied AI and Research teams to design, prototype, and deploy science-focused AI solutions in production, ensuring scalability and impact. - Own the execution of science-heavy pilot projects and proofs-of-value, demonstrating the potential of our technology in specialized domains and paving the way for full-scale deployment. Value Realization & Customer Success - Serve as a trusted advisor to customers on science-driven AI strategies , ensuring they maximize the value of their investment in Mistral's specialized capabilities. - Monitor key performance indicators (KPIs) tied to technical and business outcomes in science domains, and communicate progress to executive sponsors. - Proactively identify expansion opportunities within accounts for science applications , building on initial successes to drive long-term partnerships. Cross-Functional Collaboration - Act as the bridge between customers and Mistral's Research and Applied AI teams , synthesizing feedback to influence science-focused product and research roadmaps . - Develop reusable assets, best practices, and playbooks for science domain deployments to scale go-to-market efforts. - Travel (~30-60%) to foster deep client relationships and support on-site deployment of specialized solutions . What We're Looking For - 2+ years in a client-facing technical role (e.g., data science consulting, research engineering, or technical sales) with strong background in AI science domains (computer vision, robotics, embodied AI, etc.) - You hold a degree in a scientific field (e.g., Computer Science, Robotics, Physics, Mathematics) - PhD is a plus - Deep technical knowledge of AI/ML/Data Science with specialization in science domains , and the credibility to advise highly technical audiences - Hands-on experience building and deploying science-focused AI applications (Python, C++, or similar) to demonstrate value in specialized domains - Strong business acumen and problem-solving skills, with the ability to translate complex technical concepts into business value - Executive presence and communication skills to influence senior stakeholders (VP, C-level) on technically advanced solutions - Hands-on experience building and deploying AI applications (Python) in science domains - Resilient, results-driven, and comfortable leading through influence in a highly technical, collaborative environment - Experience with research-to-production transitions and working with research teams is a plus Why This Role Matters You will play a pivotal role in shaping how enterprises adopt and deploy AI, ensuring Mistral’s solutions deliver measurable impact. By partnering with the Applied AI team, you’ll help turn strategic visions into production-ready solutions, making Mistral an indispensable partner for our customers. Hiring Process • Talent Acquisition screening call • 30min Hiring Manager Interview • 45min Business Acumen Interview • 60min Technical Deep Dive on LLMs • Panel (Home Prep & Restitution) • 30min Value Talk • Reference check What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .
Manager, Cyber - Applied AI Architect
The Cyber Applied AI Architect Manager leads a team of customer-facing architects who partner with customers throughout the full lifecycle—from technical discovery and architecture design through implementation, deployment, and adoption. As a hands-on people leader, you’ll hire, coach, and develop the team while helping shape its technical approach and customer engagement model. You and your team will work closely with Sales and Solutions Engineering to understand customer security priorities and design AI-enabled solutions using OpenAI models, APIs, Codex, and agentic workflows. After a customer commits, your team will remain engaged to translate the proposed solution into a production-ready implementation. You’ll provide architectural guidance, support complex technical decisions and escalations, and ensure consistent delivery across customer engagements. The work spans security workflows such as secure code review, vulnerability management, threat detection, incident response, SOC operations, and GRC automation. In this role, you will: - Hire, coach, and develop a team of Cyber Applied AI Architects, setting clear expectations for technical excellence, customer impact, and career growth. - Establish team priorities, allocate resources, and balance pre-sales engagements with post-sales implementation and adoption. - Lead technical discovery with security executives, practitioners, architects, and engineering teams. - Partner with Sales and Solutions Engineering on AI solution design, demonstrations, workshops, technical validation, and proofs of concept. - Guide your team in translating customer requirements into clear solution architectures, implementation plans, success criteria, and technical milestones. - Oversee solutions from pre-sales architecture and prototyping through production deployment and adoption. - Serve as a senior technical partner for strategic customers, coordinating stakeholders and internal Product, Engineering, Security, and GTM teams. - Remain hands-on in designing, building, and troubleshooting complex integrations involving OpenAI models and APIs, Codex, agents, security tools, cloud platforms, and enterprise workflows. - Set standards for architectural reviews, evaluation frameworks, governance controls, guardrails, monitoring, and human-review processes. - Identify technical risks, resolve escalations, and turn customer feedback into actionable product and engineering priorities. - Measure team performance, customer adoption, and business impact, ensuring AI-enabled solutions deliver meaningful security outcomes. - Build reusable reference architectures, playbooks, demonstrations, and best practices that help the team scale. You might thrive in this role if you: - Have experience hiring, managing, and developing customer-facing technical teams across solutions architecture, engineering, implementation, or professional services. - Bring experience spanning both pre-sales technical engagement and post-sales delivery, with ownership of customer outcomes. - Have hands-on cybersecurity expertise across areas such as AppSec, DevSecOps, cloud security, SOC, incident response, vulnerability management, identity, or security architecture. - Can coach architects, lead executive-level technical conversations, and remain comfortable designing, building, and troubleshooting solutions. - Have experience applying AI models, APIs, or agentic patterns to practical workflows and guiding pilots into production. - Can prioritize across customer engagements, manage technical escalations, and communicate architectural decisions and tradeoffs clearly. - Enjoy building teams and operating models in ambiguous environments while taking ownership of measurable customer adoption and impact. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 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. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Applied AI Engineer
About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in Sydney, Australia. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees In this role, you will: - Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. - Design, build, and deploy AI systems that solve important customer problems and produce measurable business outcomes. - Work hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators. - Make sound technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, and governance. - Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive blockers toward resolution. - Help customers progress from promising prototypes to reliable production systems, sustained adoption, and scaled impact. - Partner closely with customer engineering teams and OpenAI Product, Research, Engineering, Security, and go-to-market teams, translating deployment experience into high-signal product feedback. - Create reusable architectures, tooling, playbooks, and technical guidance that accelerate future enterprise deployments. You’ll thrive in this role if you: - Have a demonstrated track record of designing, building, and delivering AI or machine-learning systems in enterprise environments, including taking systems from prototype to production. Relevant backgrounds may include applied AI or ML engineering, forward-deployed engineering, software engineering, customer engineering, solutions architecture, or technical consulting. - Can point to substantial personal contributions in code, architecture, evaluation, debugging, or production engineering—not only program or stakeholder management. - Are highly proficient in Python and comfortable working across an AI application stack; experience with JavaScript, TypeScript, or another relevant language is valuable. - Understand how to evaluate AI systems systematically using representative data, graders, production signals, and human judgment. - Have navigated enterprise production requirements such as integrations, reliability, observability, security, privacy, data governance, performance, and cost. - Can connect technical decisions to customer workflows, adoption, and measurable business outcomes. - Communicate with clarity and credibility across hands-on engineers, technical leaders, security teams, product leaders, and executives. - Bring high agency, strong technical judgment, and end-to-end ownership in ambiguous environments. - Learn quickly, challenge assumptions constructively, and collaborate with humility; experience in a particular industry or with OpenAI products is not required. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 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. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Product Manager, AI Applications
Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: - Creating custom AI applications that will impact millions of citizens - Generating high-quality training data for national LLMs - Upskilling and advisory services to spread the impact of AI We are looking for an entrepreneurial and experienced product leader to play a pivotal role in the ideation and development of transformative AI solutions for government and government-backed customers across the Middle East. The ideal candidate has deep experience building AI/ML applications, thinks strategically about how to solve a problem, is an excellent listener, is comfortable getting into the weeds, and has a strong understanding of software engineering principles and practices. You will own large AI projects end to end, working directly with customers and leading a cross-functional team of engineers, MLEs, and operators to deliver solutions that drive meaningful impact for our customers and significant revenue for our business. You will: - Lead design workshops with clients to define custom AI solutions - Scope new AI application use cases across government entities, and turn them into a clear roadmap, phasing, and success metrics - Build MVPs and demos to validate ideas quickly, and take the best of them to production - Lead cross-functional development with diverse stakeholders (Engineering, MLE, Operations, and Go-to-Market) - Engage consistently with end users to gather feedback and ensure we are prioritizing effectively - Scope model evaluation sets and performance requirements, review results, and iterate on the solution - Stay up to date with the latest research in applied AI and training custom LLMs - Give regular progress updates to the client and Global Public Sector leadership Ideally, you’d have: - 4+ years of experience building products, including 1–2+ years building AI-powered products in production - Strong technical background (STEM degree) and/or experience building technical software products - Hands-on experience with LLMs and applied AI, and a strong understanding of generative AI in enterprise settings - Sharp product sense and customer instinct: the conviction to take a position and defend it, and the judgment to change it when the evidence says so - Comfort with client-facing work and the pace and ambiguity of a forward-deployed team - Experience with vibe coding tools (e.g., Replit, Lovable, Bolt) and design tools (e.g., Figma, Canva, Miro) - Exceptional leadership, presentation, and communication skills, with the ability to influence cross-functional teams Nice to haves: - Proficiency in Arabic, both written and spoken - Coding experience (Python) - Prior experience as a founder, founding engineer, or forward-deployed PM - Experience working with government or GCC customers PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Principal Software Engineer, GPS
Principal Software Engineer, Global Public Sector Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: - Creating custom AI applications that will impact millions of citizens - Generating high-quality training data for national LLMs - Upskilling and advisory services to spread the impact of AI We are hiring a Principal Engineer to join a small team of our most senior engineers who take on the problems no one else can. You will work at the earliest stage of our engagements: shaping the technical approach with clients, defining the technology we build on, and turning ideas into working prototypes fast. You will step in when a project is stuck or a problem is unusually hard, and turn what you learn in the field into shared capabilities every team can build on. This is a very senior, hands-on role. Our engineering organisation is young, so mentoring is a core part of the job: you will raise the bar for how we design, build and deliver, and grow the next generation of technical leaders around you. The role is based in London. At Scale, we’re not just building AI solutions, we are building repeatable blocks to enable the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a member of our rapidly expanding team, we’d love to hear from you. You will: - Take on the hardest technical problems across our programs, stepping in where projects are stuck or the path forward is unclear - Lead the technical side of early engagements: work with clients to scope problems, shape proofs of concept and keep the scope needed to prove value as small as possible - Build working prototypes quickly, from AI agents and evaluation pipelines to data and knowledge systems, and take the most promising ones to production - Define the technology and architecture our solutions are built on, keeping them cohesive, secure and reusable across clients - Mentor engineers across a young organisation through pairing, design and code reviews, and set the bar for engineering excellence - Partner with Directors, VPs and client executives to navigate high-stakes business and technical trade-offs, including travel to client sites as engagements require - Turn patterns from the field into reusable capabilities, contributing components back to our core platform so every engagement starts further ahead - Lead from the front on agentic engineering, both in the AI systems we build and in how our teams use coding agents day to day, and push the boundaries of what’s possible with AI Ideally you’d have: - A strong engineering background, with a Bachelor’s degree in Computer Science, Mathematics or a related quantitative field (or equivalent practical experience) - 10+ years of post-graduation engineering experience, with demonstrated proficiency in languages such as Python, TypeScript/JavaScript, Java, or C++ - 5+ years of experience applying AI/ML in production environments, such as building generative/agentic AI applications, RAG systems or evaluation pipelines - Strong problem-solving skills, with a track record of taking ambiguous, early-stage problems from a blank page to a working prototype and into production - Deep expertise in system design and architecture, including experience with cloud-based machine learning tools and platforms (e.g. AWS, GCP, Azure) - Experience mentoring engineers and raising the technical bar of a team or organisation - Comfort working directly with clients, from their engineering teams to senior executives - Excellent written and verbal communication skills to collaborate effectively in a cross-functional environment Nice to haves: - Past experience in a forward deployed engineering role - Experience working at a startup, particularly as a founding engineer - Experience building and deploying large-scale AI solutions - Experience delivering technology programs for governments or regulated industries - Experience deploying solutions on-prem or in customer-controlled environments - Current or previous UK government security clearance (e.g. SC or DV) PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world’s most important decisions. Our products provide the high-quality data and full-stack technologies that power the world’s leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Applied AI Engineer
About the role Scale's Global Public Sector team uses AI to address critical challenges facing the public sector around the world. As an Applied AI Engineer, you'll build AI that runs inside production systems used by national health and government organisations. You'll own scoped components of those systems, such as a model integration, agent tool, API, data pipeline, or evaluation, from implementation through to delivery. Senior engineers set the system-level design and client commitments, so you can go deep on making your components work reliably on real data. What you'll do - Own the implementation, testing, and delivery of defined AI components within an established system design - Build agent tools, model integrations, and the backend services and APIs they depend on - Run and extend evaluations within an established framework, interpret results, investigate common failure modes, and flag regressions - Debug production issues in the components you own and resolve them using the team's engineering practices - Communicate progress and blockers early, and take responsibility for delivery dates within your scope - Work directly with client teams on the requirements and feedback for your components - Share what you learn with the team as you build public sector domain expertise What we look for - Experience building and shipping production software, with proficiency in Python and working knowledge of at least one of TypeScript, Java, or C++ - Hands-on experience integrating models or AI/ML components into a production application, such as calling LLMs, building retrieval or agent tooling, or deploying a trained model - A working understanding of ML evaluation: how to read results, spot regressions, and identify common causes of model failure - Experience owning a defined piece of work through testing, release, and production debugging - Strong problem-solving skills and a data-driven approach to iterating on models and datasets - Clear written and verbal communication, including raising blockers and trade-offs early Nice to have - A backend or full-stack engineering background, so you can work across the API, service, and data-schema layers of the systems you contribute to - Experience with cloud ML platforms such as AWS, GCP, or Azure - Exposure to agentic workflows, retrieval-augmented generation, or context engineering - Experience handling regulated or sensitive data Where this role sits Your primary accountability covers production AI behaviour, its backend integration, and the evaluation required for a specific customer. Senior Full-Stack Engineers own the complete user-facing application and its infrastructure. ML Research Engineers lead novel agent architecture and the benchmark methodology used across accounts. The roles work together on agents and evaluation, with accountability set by the scope of the problem. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Applied AI Engineer, Enterprise - Healthcare Life...
About the Team Across industries, OpenAI’s Applied AI Engineering (AIE) team helps organizations turn frontier AI into safe, reliable production systems that deliver meaningful business outcomes. We work directly with customers’ engineering, product, security, and transformation teams to navigate complex architectures, data environments, governance requirements, and organization-wide change. We turn lessons from these deployments into better OpenAI products and reusable patterns that help customers move faster. About the Role As an Enterprise AIE, you will serve as a technical partner to leading organizations within the Healthcare and Life Sciences segment (HLS), helping them turn ambitious AI use cases into durable production systems and adoption at scale. You will combine deep technical judgment with hands-on engineering to provide technical leadership on complex customer deployments. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions about model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. You will work across clinical, operational, administrative and research workflows, translating security, privacy and governance requirements into practical deployment decisions. Success is measured by durable production systems, sustained adoption, and meaningful business impact. Your deployment experience will also directly influence how OpenAI’s products evolve. This role may be based in one of our offices in New York City or San Francisco, or it may be performed remotely. Office-based employees follow a hybrid work model with three days per week in the office. We offer relocation assistance to new employees. In This Role, You Will - Work hands-on in code to design, build, evaluate, and deploy AI systems from prototype to reliable production and scaled adoption that solve important customer problems and deliver measurable business outcomes. - Partner with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and success criteria. - Make sound technical decisions across model selection, agent and tool design, retrieval, context design, data pipelines, evaluation, reliability, observability, latency, cost, safety, security, and governance. - Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive blockers to resolution. - Partner closely with customers’ engineering teams and OpenAI’s Product, Research, Engineering, Security, and Go-to-Market teams to turn deployment experience into actionable product feedback. - Partner with customer security, privacy, clinical and business teams to design responsible AI deployments, including data handling, access controls, evaluation, human oversight and monitoring. - Create reusable architectures, tooling, playbooks, and technical guidance that accelerate future enterprise deployments. You Might Thrive in This Role If You - Have personally designed, built, and shipped AI or machine-learning systems in enterprise environments, taking them from prototype to production and making substantial contributions through coding, architecture, evaluation, debugging, or production engineering. Relevant backgrounds may include applied AI or ML engineering, forward-deployed engineering, software engineering, customer engineering, solutions architecture, or technical consulting. - Are highly proficient in Python and comfortable working end to end across model APIs, agent and tool development, retrieval and data pipelines, evaluation, observability, integrations, and production operations. Experience with JavaScript, TypeScript, or another relevant language is valuable. - Know how to evaluate AI systems systematically using representative data, automated graders, production signals, and human judgment. - Have navigated enterprise production requirements, including integrations, reliability, observability, security, privacy, data governance, performance, and cost. - Have experience delivering AI or software in healthcare, life sciences or similarly complex regulated enterprises, with measurable outcomes beyond a proof of concept and familiarity with sensitive data, legacy systems and interoperability. - Can connect technical decisions to customer workflows, adoption, and measurable business outcomes. - Communicate clearly and credibly with hands-on engineers, technical leaders, security and product teams, and executives. - Take end-to-end ownership, exercise strong technical judgment, and move effectively through ambiguity. - Healthcare or life sciences experience is strongly preferred; strong candidates from other regulated enterprise environments are also encouraged to apply. - Learn quickly, challenge assumptions constructively, and collaborate with humility. Prior OpenAI product experience is not required. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 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. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Applied AI Engineer, Enterprise - EDU
About the Team Across industries, OpenAI’s Applied AI Engineering (AIE) team helps organizations turn frontier AI into safe, reliable production systems that deliver meaningful business outcomes. We work directly with customers’ engineering, product, security, and transformation teams to navigate complex architectures, data environments, governance requirements, and organization-wide change. We turn lessons from these deployments into better OpenAI products and reusable patterns that help customers move faster. About the Role As an Enterprise AIE, you will serve as a technical partner to leading organizations including universities and other educational institutions, helping them turn ambitious AI use cases into durable production systems and adoption at scale. You will combine deep technical judgment with hands-on engineering to provide technical leadership on complex customer deployments. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions about model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by durable production systems, sustained adoption, and meaningful business impact. Your deployment experience will also directly influence how OpenAI’s products evolve. This role may be based in one of our offices in New York City or San Francisco, or it may be performed remotely. Office-based employees follow a hybrid work model with three days per week in the office. We offer relocation assistance to new employees. In This Role, You Will - Work hands-on in code to design, build, evaluate, and deploy AI systems from prototype to reliable production and scaled adoption that solve important customer problems and deliver measurable business outcomes. - Partner with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and success criteria. - Make sound technical decisions across model selection, agent and tool design, retrieval, context design, data pipelines, evaluation, reliability, observability, latency, cost, safety, security, and governance. - Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive blockers to resolution. - Partner closely with customers’ engineering teams and OpenAI’s Product, Research, Engineering, Security, and Go-to-Market teams to turn deployment experience into actionable product feedback. - Create reusable architectures, tooling, playbooks, and technical guidance that accelerate future enterprise deployments. You Might Thrive in This Role If You - Have personally designed, built, and shipped AI or machine-learning systems in enterprise environments, taking them from prototype to production and making substantial contributions through coding, architecture, evaluation, debugging, or production engineering. Relevant backgrounds may include applied AI or ML engineering, forward-deployed engineering, software engineering, customer engineering, solutions architecture, or technical consulting. - Are highly proficient in Python and comfortable working end to end across model APIs, agent and tool development, retrieval and data pipelines, evaluation, observability, integrations, and production operations. Experience with JavaScript, TypeScript, or another relevant language is valuable. - Know how to evaluate AI systems systematically using representative data, automated graders, production signals, and human judgment. - Have navigated enterprise production requirements, including integrations, reliability, observability, security, privacy, data governance, performance, and cost. - Experience navigating education or research environments, including institutional data, privacy, access controls and complex integrations, is valuable. - Can connect technical decisions to customer workflows, adoption, and measurable business outcomes. - Communicate clearly and credibly with hands-on engineers, technical leaders, security and product teams, and executives. - Take end-to-end ownership, exercise strong technical judgment, and move effectively through ambiguity. - Learn quickly, challenge assumptions constructively, and collaborate with humility. Experience working with education institutions, particularly universities, is preferred but not required. Prior OpenAI product experience is not required. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 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. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
AI Scientist - Domain Expert Crashworthiness
About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About the job Mistral AI is looking for a Domain Expert in crashworthiness simulations to help build AI-accelerated simulation capabilities for industrial engineering. You will work at the intersection of industrial simulation, physics modeling, machine learning, and engineering workflows. Your role is to bring deep solid-mechanics expertise into the design, training, evaluation, and deployment of AI Physics Models for real engineering use cases. This is a hands-on technical role. We are looking for someone who understands industrial structural simulation not only conceptually, but through direct experience with simulation models, solver workflows, data generation, validation, and engineering decision-making. You will work with research, product, and customer-facing teams to ensure that our models are useful against real engineering standards — not only benchmark metrics. Relevant application areas may include automotive crashworthiness, aerospace structures, consumer-electronics drop/reliability, manufacturing, durability/fatigue, and other nonlinear structural mechanics problems. What you will do - Work with our research team to define, generate, and iteratively improve simulation datasets for training and evaluating crashworthiness foundation models, balancing coverage of relevant physical scenarios, simulation fidelity, and computational cost. - Design and run high-fidelity simulation campaigns using structural mechanics solvers such as Abaqus, LS-DYNA, Ansys Mechanical, Radioss or equivalent tools. - Define the relevant variation space for training data: geometry, mesh resolution, material behavior, boundary conditions, loading, contact, joints, failure modes, and engineering KPIs. - Build or guide automated pipelines for simulation setup, execution, post-processing, dataset creation, and model evaluation. - Work with research teams to train and evaluate AI models on simulation data, and diagnose failure modes caused by data gaps, poor coverage, numerical artifacts, or model limitations. - Evaluate model outputs against industrial engineering needs, including field-level accuracy, scalar KPIs, deformation modes, load paths, energy absorption, stress/strain fields, failure indicators, uncertainty, and out-of-domain behavior. - Work with industrial customers to understand their simulation workflows and engineering priorities, define use cases and success criteria, and incorporate their feedback into model development and validation. About you - You have deep expertise in crashworthiness, solid mechanics, and structural mechanics, with substantial experience in industrial simulation workflows. - You have a Master’s degree or equivalent technical depth in mechanical engineering, aerospace engineering, civil/structural engineering, computational mechanics, applied physics, or a related field. - You have 4+ years of relevant industrial experience (or PhD +1 years) in domains such as automotive, aerospace, and consumer electronics. - You have hands-on experience with explicit dynamics for crash or impact simulation and understand nonlinear FEM and related topics such as contact, plasticity, structural dynamics, buckling, material modeling, fracture/damage, fatigue, crashworthiness, or durability. - You have direct experience with simulation validation, correlation, model quality, numerical sensitivity, and engineering KPI definition. - You are a strong Python developer who can build and maintain reliable tools for simulation automation, data processing, and model evaluation. You apply sound software engineering practices, including version control with Git, automated testing, code review, and clear documentation. - You have hands-on experience working in Linux and HPC environments, including submitting and monitoring batch jobs, selecting appropriate compute resources, and troubleshooting simulation workflows. You can run simulation campaigns efficiently across a compute cluster. - You are comfortable operating in ambiguous technical environments and turning poorly defined industrial problems into scoped datasets, experiments, metrics, and execution plans. - You communicate clearly with both deep technical experts and non-specialist stakeholders. It would be great if you - Have experience applying machine learning, surrogate modeling, reduced-order modeling, optimization, or data-driven methods to simulation problems. - Have contributed to reusable internal tools, open-source code, simulation automation frameworks, or production-quality engineering workflows. - Have experience working directly with industrial customers, product teams, or engineering decision-makers. - Have publications, patents, internal technical leadership, or recognized contributions in engineering, simulation, computational mechanics, or ML-for-physics communities. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .
Field Execution Partner, Account Executives
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 field-tested sales operator to serve as the dedicated execution and enablement partner for our global Account Executive (AE) organization. As part of Revenue Operations, you'll design the programs and lead the change that keep this team sharp, consistent, and ahead of the curve as Fireworks scales. This role requires deep domain experience as a former quota-carrying Account Executive. You'll pair sales credibility with business-operations rigor to bring a clear point of view on what great looks like and the program discipline to make changes stick globally. You'll also use your own AI fluency to bring agentic workflows into how AEs work day to day. Your success will be measured in AE outcomes: time-to-first-deal and ramp compliance for new hires, and ramped AE Productivity. Please Note: This is an individual contributor role reporting to the Head of GTM Enablement. Expect ~15–20% travel for team events and trainings. What You'll Own - Embed in AE leadership and drive critical change management initiatives: Take a standing seat in AE leadership forums, where you'll help shape the segment's go-to-market strategy alongside your RevOps counterpart. As the operating model evolves, you'll drive the execution of the team's most critical initiatives, whether that's a multi-quarter transformation or a fix shipped in days. - Own deal-execution excellence for tenured AEs: Keep experienced AEs sharp with a continuous cadence of AE-specific enablement centered on how we sell: deal strategy, forecasting discipline, and positioning consumption-based pricing. You'll also build the product and AI/ML fluency AEs need to run credible discovery and know when to bring in an AI Field Engineer. - Optimize the AE ramp program and own the outcomes for new AEs: Audit and continuously improve the AE onboarding experience, from our Firecademy onboarding program through full ramp, and make sure every new AE ramps consistently, wherever they sit. You'll be measured on time-to-first-deal and new hire ramp compliance. - Surface and scale AE best practices: Pinpoint what top AEs do differently through call reviews, field conversations, and pipeline and win/loss data. Then scale those patterns across the team with programs like peer showcases, deal reviews, and a curated call library, and feed what you learn back into the broader go-to-market team. - Build the AI tools AEs use on live deals: Design and ship AI agents that work inside the AE workflow, such as account research, call preparation, and deal-strategy coaching, so AEs move faster with customers. Minimum Qualifications - 8+ years of experience, including significant time as a quota-carrying Account Executive selling to enterprise buyers - Working fluency in AI/ML or developer infrastructure, and the credibility to coach sellers who work with technical buyers - A track record of driving change across a team, with the rigor to define, track, and act on the metrics that prove it worked - Strong at both content development and live facilitation, from new-hire cohorts to experienced sellers - Has personally built AI agents or apps, through prompting, no-code, low-code, or code, to drive seller or operational productivity (engineering degree not required) - Thrives in ambiguity, high ownership, and the pace of a high-growth startup - Based in AMER and willing to travel ~15–20% Preferred Qualifications - Experience as a first- or second-line sales leader, or as Chief of Staff to a GTM leader - AE experience at an AI/ML infrastructure, developer tools, or API-first and consumption-based business, with literacy in usage-based pricing models - Prior ownership of onboarding, ramp, or enablement programs for sellers - Fluency in enterprise sales methodologies (e.g., Command of the Message, MEDDICC) and forecasting discipline - Familiarity with modern enablement tooling and systems (LMS, CMS, CRM, conversation intelligence) 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.
Customer Trust Specialist
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 looking for a Customer Trust Specialist to join our London office and help run the customer-facing side of our trust program. Where our GRC team keeps the compliance engine running behind the scenes, you'll be one of the people customers actually interact with, turning our security, privacy, and AI-governance posture into accurate answers that earn trust. You'll handle security questionnaires end to end, help operate our trust automation platform, and support customer conversations across EMEA and beyond. This is a great fit for someone with solid security-review experience who wants to grow their scope at a fast-scaling AI company. What you'll do - Handle security questionnaires end to end: intake, drafting, review, and delivery for customer security assessments, RFPs, and vendor evaluations, in whatever format they arrive (OneTrust, spreadsheets, portals, email), pulling in Security, Legal, or Engineering when an answer needs it. - Operate our trust automation platform: use and help improve the system that generates answers from our governed knowledge base. Review output for accuracy, flag weak or incorrect answers, and help keep the guardrails from over-claiming. - Keep the knowledge base current: update answers as the platform, certifications, and control environment change; ingest new evidence (SOC 2, ISO 27001/27701/42001, HIPAA, penetration tests); and flag stale facts before they reach a customer. - Handle one-off customer requests: evidence requests, Trust Center access, point questions from account teams, and anything that doesn't fit a questionnaire but still shapes a customer's confidence. - Support customer calls: join prospect and customer calls alongside Sales and Solutions to field security, privacy, and AI-safety questions, especially for UK and EMEA customers. Partner with the sales team from intake through close. - Support contract reviews: work with Legal and Deal Desk on security and privacy terms in DPAs and MSAs, including UK GDPR and EU data-transfer questions; learn which positions are standard and which need escalation. - Keep the program honest: follow the standing rules that protect us and our customers: state only our standard position, never reference another customer's ask or situation, and escalate anything that needs Legal, Security, or Engineering sign-off. - Track program data: log knowledge-base gaps, recurring questions we can't answer well yet, and where automation is saving or costing time, and share findings with the team. - Help maintain public trust artifacts: keep the Trust Center, security whitepapers, and supporting evidence current and aligned with what we actually do. How the role will grow As you build context on our platform and customers, you'll take on more ownership: - Broader program ownership: lead specific parts of the program, such as a framework area, a slice of the knowledge base, or EMEA customer coverage. - AI-assurance coverage: help extend the knowledge base to emerging standards like ISO 42001, NIST AI RMF, and the EU AI Act. - Cross-functional influence: work more closely with Product, Engineering, Legal, and Sales to make our security and AI-safety posture a differentiator rather than a checkbox. What we're looking for - 3 to 5 years of experience in customer-facing security, trust, or GRC roles: security assurance, customer trust, vendor security review, security-focused sales engineering, or similar. - Hands-on experience with security questionnaires and the customer security-review process across formats (CAIQ, SIG, custom spreadsheets, OneTrust and similar portals) and frameworks (SOC 2, ISO 27001, GDPR/UK GDPR, NIST). - Some exposure to contracts (DPAs, MSAs) and the ability to connect contract language to a company's actual security controls. - Strong written communication; you can turn a control requirement into a clear, accurate answer, and you know the difference between answering a question and over-answering it. - Working knowledge of cloud environments (AWS, GCP, or Azure) and SaaS architectures; comfortable discussing encryption, isolation, and data flows with technical buyers. - Interest in trust automation and AI-assisted tooling, with an understanding that automation needs guardrails. - A precise, detail-oriented mindset; you catch the answer that is almost right, and you treat a customer-facing representation as something that has to be true. - A collaborative, low-ego approach, and good judgment about when to escalate rather than answer. - Comfortable working with a US-based team, including some overlap with US Eastern hours. - Bonus: familiarity with AI/ML platforms, LLM inference, or AI governance concepts (zero data retention, content guardrails, EU AI Act). 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.
Enforcement Analyst, Agentic Alignment
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and society as a whole. As an Enforcement Analyst focused on Agentic Alignment, you will play a crucial role in identifying and investigating harmful and unexpected behavior by models, and make enforcement decisions accordingly. You'll work closely with a suite of cross-functional teams, within and outside of Safeguards, including: Policy, Threat Intel, Engineering, Research, and Transparency. Your work will be essential in maintaining Anthropic's commitment to safe and beneficial AI as Claude takes on more autonomous work. Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. There is also an on-call responsibility across the Policy and Enforcement teams. Key responsibilities - Review and investigate potential instances of Agentic Misalignment, working from transcripts, tool-use traces, and code - Triage cases by severity and urgency and share through the appropriate channels - Help operationalize review pipelines for agentic cases, translating leads from detection outputs and investigations into structured review workflows that scale - Make enforcement decisions under the Usage Policy, applying it consistently to novel agentic scenarios and across surfaces, and documenting the reasoning behind each decision - Assess cyber-related agentic activity, such as scanning, exploitation attempts, credential misuse or malicious code to determine its real-world harm potential - Write clear, well-evidenced case write-ups for audiences ranging from enforcement peers to senior leadership - Identify patterns and trends across cases, and close the loop between enforcement outcomes and upstream improvements by feeding findings back to policy, detection and research teams to improve policies, classifiers and model behavior - Maintain rigorous documentation of enforcement decisions, review logic and precedents to build institutional knowledge - Collaborate with Threat Intelligence, Research, Engineering and Policy partners so that detection coverage keeps pace with how agentic misuse and misaligned behavior evolve - Use AI systems, including Claude, to accelerate your own investigations: summarizing long transcripts, analyzing code, querying data and building lightweight tooling - Contribute to regular reports on agentic harm trends and enforcement outcomes Minimum qualifications - Can read and understand code (for example Python, JavaScript or shell scripts) well enough to follow what happened and why it matters - Have a background in security, cyber threat intelligence, or a similar technical field that lets you understand how cyber harm happens and judge its severity - Have experience in trust and safety, enforcement, investigations or a related field, translating ambiguous policy questions and facts into defensible enforcement decisions and clear written findings - Have conducted structured investigations, building a case from first signal to final finding and knowing when the evidence is strong enough to act on - Have supported or contributed to formal enforcement actions, including case documentation, evidence packaging and escalation coordination - Write clearly and concisely, and can present complex findings to stakeholders across Legal, Policy and Engineering, including non-technical audiences - Have sound judgment about when a case needs escalation, and the resilience to work with difficult content Preferred qualifications - Have demonstrated use of AI systems to accelerate your own work, and are excited to keep finding new ways to do so - Are comfortable working with large volumes of data, from long transcripts, logs and traces to complex, multi-table datasets, and surfacing the behavioral patterns that matter - Are curious about how AI agents behave, and enjoy investigating behavior no one has categorized before, building approaches where established playbooks don’t exist - Have familiarity with AI safety and alignment, and current debates about the risks of increasingly autonomous AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $245,000 - $285,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Staff Software Engineer, AI Developer Tooling
Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will redefine how engineers develop, build, test, and deploy software at Scale using AI development tools in addition to traditional practices. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: - Define next-generation AI development tooling and frameworks using products like Cursor, Claude Code, OpenAI Codex, and MS Copilot, as well as in-house custom-built solutions. - Drive the architecture, design, and implementation of our local development process, build, test, continuous integration, and continuous delivery systems, working closely with stakeholders and internal customers to understand and refine requirements. - Directly mentor software engineers ranging from new grads to experienced engineers. - Proactively identify opportunities and drive improvements to software development practices, processes, tools, and languages. - Present technical information to teams and stakeholders, providing guidance and insight on development processes and technologies. Ideally you’d have: - 8+ years of full-time engineering experience, post-graduation, with experience in build, test, or CI/CD systems. - Extensive experience defining and evangelizing best-practices for AI development tools, including cost guardrails, security frameworks, and hosting knowledge-sharing sessions, among others. - Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS preferred). - Experience configuring, testing, and enabling MCP servers, AI agents, and other associated systems. - Show a track record of independent ownership of successful engineering projects. - Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders. - Experience working fluently with standard infrastructure, containerization, and deployment technologies like Terraform, Docker, Kubernetes, etc. - Experience with modern web frameworks like NodeJS, NextJS, etc. - Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI, Helm, ArgoCD). Nice to haves: - Experience scaling products at hyper-growth startups. - Experience with modern build systems like Bazel, Buck, Pants, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $252,000 - $315,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Recruiter, Applied AI
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking a strategic Go-To-Market Recruiter specializing in Applied AI to join our GTM recruiting organization. In this role, you'll focus specifically on building and scaling our Applied AI team - the Pre-Sales architects and technical advisors who help large enterprises successfully integrate and deploy Claude. Working within our broader GTM recruiting team, you'll drive full-cycle recruiting for these critical customer-facing technical roles that bridge our cutting-edge AI technology with real-world business applications. This specialized role requires deep technical recruiting expertise combined with a strong understanding of enterprise SaaS and AI landscapes. You'll collaborate closely with GTM recruiting colleagues while developing targeted strategies for the unique talent needs of our Applied AI organization. You'll help shape how enterprises work with AI systems by building teams that directly influence the safe and beneficial deployment of Claude across industries. Key responsibilities - Lead end-to-end recruiting for Applied AI team roles, including Solutions Architects, Pre-Sales Engineers, front-line managers and other customer-facing technical positions - Partner with Applied AI leadership and GTM recruiting colleagues to develop comprehensive hiring strategies that align with overall GTM objectives - Execute sophisticated sourcing strategies to identify candidates with rare combinations of technical depth, customer empathy, and business acumen - Create exceptional candidate experiences that showcase Anthropic's mission and the unique opportunity to shape enterprise AI adoption - Build pipelines of talent with expertise in LLMs, cloud architecture, enterprise software integration, and technical consulting - Collaborate with GTM recruiting team members to share best practices, market insights, and cross-functional candidate leads - Leverage Claude and other AI tools to enhance recruiting efficiency while maintaining high-touch, personalized engagement - Provide data-driven insights on compensation trends and talent availability specific to the Applied AI market Minimum qualifications - Excel at recruiting for customer-facing technical roles that require both deep technical knowledge and exceptional communication skills - Understand the technical requirements of roles working with LLMs, APIs, cloud architectures, and enterprise system integration - Thrive in collaborative environments, working seamlessly with GTM recruiting colleagues while managing specialized searches - Can effectively assess candidates' abilities to translate complex technical concepts for diverse stakeholders - Have a track record of building trusted advisor relationships with technical hiring managers - Are passionate about using AI to transform recruiting practices while maintaining a human-centered approach Preferred qualifications - Have 5+ years of technical or technical sales recruiting experience, ideally within GTM organizations at enterprise software or AI/ML companies - Direct experience recruiting for pre-sales/solutions engineering roles in the AI/ML space - Demonstrated success working within GTM recruiting organizations during periods of hypergrowth - Expertise in developing specialized recruiting practices within broader team structures - Familiarity with the challenges of deploying AI systems in enterprise environments - Experience collaborating across recruiting teams to share resources and best practices - A technical background or successful track record recruiting for highly specialized technical positions The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $175,000 - $240,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Applied AI Architect, Democratic Partnerships
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a member of the Applied AI, Democratic Partnerships team at Anthropic you will provide technical support to the governments of key international allies and civil-sector partners to support democratic resilience. Near-term work focuses on a few priority countries and partners, and will continue to expand with capacity. This role serves Anthropic's mission and public benefit goals. In collaboration with the Policy, National Security, Product, Research, and Engineering teams, you'll help partners build, integrate, and ship Claude deployments. You will use your excellent communication skills to explain complex topics, including the potential benefits and harms of frontier AI, to technical and non-technical audiences alike. You will also play a critical role in identifying how our AI systems can best serve public interests in frontline democracies, while maintaining our best-in-class safety standards. Responsibilities: - Work directly with partner technical teams to build and ship Claude deployments. Guide their setup, architecture, and integration as they build with Claude Code and the Claude API. - Build pilots and repeatable workflows that can scale across partner agencies, and support developer and university enablement. - Document how to deploy Claude in low-connectivity, multilingual, and security-conscious environments, for reuse across partners. - Act as the voice of our partners in frontline democracies and a key collaborator with our Product and Research teams to ensure we deliver the capabilities they need. - Travel internationally to partner institutions for technical enablement and building relationships. - Establish a shared vision for creating solutions that enable beneficial and safe AI. - Lead the vision, strategy, and execution of innovative solutions that leverage our latest models’ capabilities. - Support partner deployments in areas such as education, cyber resiliency and global health. You may be a good fit if you have: - 4+ years of experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Cybersecurity Engineer, working with governments, civil-sector organizations, or the public sector - Experience shipping software in imperfect conditions, and a practical approach to infrastructure constraints - Designed novel and innovative solutions for technical platforms in a developing mission area - Comfort working directly with partner technical teams, and motivation to work on deployments where the stakes are civic rather than commercial - Strong technical aptitude to partner with engineers and strong proficiency in at least one programming language (Python preferred) - Understanding of and experience with LLM fundamentals - The ability to navigate and execute amidst ambiguity, and to flex into different domains based on the problem at hand, finding simple, easy-to-understand solutions - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders, from engineers to senior government officials - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 - $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Applied AI Architect, Beneficial Deployments (Glob...
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Beneficial Deployments Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most. About the Role We're looking for an Applied AI Architect to join Beneficial Deployments, focused on helping public health, global health and humanitarian organizations get real value from Claude. You'll be the technical lead for partners such as public health agencies and ministries of health, the institutes and NGOs that support them, and humanitarian organizations working in crisis settings. You'll help them find where Claude makes a real difference, from disease surveillance and outbreak response to health data, communications and program delivery, design solutions that fit their data, privacy and procurement rules, and turn early pilots into lasting deployments. What works for one partner becomes something the whole field can use. Responsibilities - Serve as the primary technical advisor to a portfolio of health partners from discovery through deployment, turning their priorities into scoped use cases with clear measures of success. - Design and demo solutions with Claude, the API, Claude Science and Claude Code across surveillance, outbreak response, data analysis and public communications. - Guide partners through security review, data governance and procurement, from national agencies to field operations. - Run workshops, trainings and tabletop exercises that build AI fluency across partner teams. - Build reusable assets (reference designs, connectors, prompt and eval templates) so one partner's work helps the next. - Spot patterns across partners, bring field insight back to Product and Research, and help partners measure what changed. - Travel to partner sites for workshops, technical deep dives and relationship building. You Might Be a Good Fit If You Have - 3+ years in customer-facing technical roles such as solutions architecture, sales engineering, forward-deployed engineering or technical consulting. - Experience working with public health agencies, ministries of health, global health or humanitarian organizations, or similarly complex public institutions, including how they buy, adopt, and govern technology. - A track record of making technology stick inside slow-moving organizations with many stakeholders. - Hands-on experience building with LLM APIs: you can prototype a working demo. You don't need to write production code. - Clear written and spoken communication across a broad audience. The ability to explain technical tradeoffs to epidemiologists, program leads, field teams and executives. - Patience with long buying cycles, a knack for knowing how to make them go smoothly, and real care for public benefit. - Comfort operating in ambiguity: you bring clarity to fuzzy problems, wear multiple hats and do whatever it takes to further the mission. - Bonus if you've worked on disease surveillance, outbreak response, health information systems or emergency operations. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 - $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Applied AI Architect, International Policy
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a member of the International Policy Applied AI team at Anthropic, you will be a trusted technical advisor to governments, AI Safety Institutes (AISIs), and multilateral institutions. You'll use your technical skills and your experience with government partners to help them understand frontier AI, test it, and apply it to their public missions with a high degree of reliability and safety. This role serves Anthropic's policy, mission, and public benefit goals. In collaboration with the Policy, Product, Research, and Engineering teams, you'll help partners develop strategies and plans to evaluate and adopt leading-edge AI systems. You will use your excellent communication skills to explain complex topics, including the potential benefits and harms of frontier AI, to technical and non-technical audiences alike. You will also play a critical role in identifying how our AI systems can best serve public interests around the world, while maintaining our best-in-class safety standards. Responsibilities: - Act as a primary technical advisor for senior officials in partner governments, AISIs, and international institutions. Brief them on frontier AI capabilities, give an honest account of both benefits and harms, and explain safety research in terms that inform their decisions. - Partner closely with the Policy team to understand each partner's goals and requirements. Develop demos, pilots, prototypes, and evaluation suites that show how Claude can support their public missions, such as cyber defense. - Lead technical onboarding, enablement, and hands-on workshops for partner institutions, including national cybersecurity agencies. Guide their setup, architecture, and integration as they build with Claude Code and the Claude API. - Act as the voice of our international partners and a key collaborator with our Product and Research teams to ensure we deliver the capabilities they need. - Travel internationally to partner institutions for senior leader meetings, technical enablement, and building relationships. - Establish a shared vision for creating solutions that enable beneficial and safe AI. - Lead the vision, strategy, and execution of innovative solutions that leverage our latest models’ capabilities. You may be a good fit if you have: - 4+ years of experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Cybersecurity Engineer, working with governments, international organizations, or the public sector - Experience in technology policy, AI safety, cybersecurity, or international affairs - Designed novel and innovative solutions for technical platforms in a developing mission area - Familiarity with how AI models are evaluated and tested for safety - Strong technical aptitude to partner with engineers and strong proficiency in at least one programming language (Python preferred) - Understanding of and experience with LLM fundamentals - The ability to navigate and execute amidst ambiguity, and to flex into different domains based on the problem at hand, finding simple, easy-to-understand solutions - Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities - Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders, from engineers to senior government officials - Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 - $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Applied Scientist, Engineering
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Discovery team at Anthropic is organized around the north star goal of building an AI scientist – a system capable of solving the long-term reasoning challenges and basic capabilities necessary to push the scientific and technological frontier. We're expanding our work on engineering and the applied sciences. Our goal is to contribute to training Claude to invent, design, and engineer across every discipline and scale, reliably and safely: new manufacturing and experimental techniques, processes, materials, devices, instruments, machines, energy systems, and factories. We want this work to accelerate science and technology and benefit people widely. We're seeking exceptional researchers with deep expertise in one or more of these areas. In this role, you'll work at the intersection of frontier AI and your field, developing rigorous methods to measure and improve Claude's performance on complex engineering and scientific tasks. You'll collaborate closely with researchers, engineers, and partners across Anthropic and industry to build AI systems that can engage in all phases of research and development, and to test Claude's designs against real-world feedback. Key responsibilities - Design and implement evaluation methodologies for assessing AI model capabilities relevant to engineering and applied science research and applications - Design realistic tasks and training environments, and curate data from your field - Develop and validate simulations and computational tools for your field, and calibrate them against real-world data - Work with industry partners, manufacturers, and labs to build and test what Claude invents, designs, and engineers, and bring that real-world feedback into evaluation and training - Think through how Claude's engineering capabilities can permeate the real world: where they can have the most impact across industry and research, and what it takes to get them adopted - Advise the team on which problems, tools, and workflows matter most in your field - Collaborate with domain experts and partners to establish benchmarks and gather high-quality data for training - Translate between engineering domain knowledge and machine learning objectives Minimum qualifications - Deep expertise and hands-on R&D or industry experience in an engineering or applied science discipline, such as mechanical, electrical, materials, chemical, aerospace, structural, industrial, or manufacturing engineering; applied physics; computational simulation - Experience with AI or machine learning, whether evaluating and training AI systems or applying these tools in your field - Track record of taking work from concept through to a working result, such as a product, process, device, experiment, or tool - Hands-on proficiency with the computational design, analysis, or simulation tools used in your field - Basic programming proficiency, for example in Python - Ability to navigate ambiguity and develop solutions in a rapidly evolving research environment - Ability to work independently while collaborating closely with cross-functional teams, and to explain your field clearly to people outside it - Commitment to using AI to accelerate engineering and scientific progress while maintaining high ethical standards Preferred qualifications - 5+ years of hands-on R&D or industry experience in an engineering or applied science discipline - Ph.D. in an engineering or applied science field, or equivalent industry experience - Industry experience in product design and manufacturing, or in developing engineering or scientific simulation software - Breadth across more than one discipline, or across several stages of the path from design to production - Familiarity with modern AI model training methods - Track record of building high-fidelity solvers or simulation engines that were validated against real-world data and used in practice - Experience working with manufacturers, vendors, contract research organizations, or academic labs - Experience managing data pipelines and working with large-scale technical datasets - Publications, patents, or contributions to open-source scientific or engineering software The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 - $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Member of Technical Staff (AI Software Engineer, A...
Perplexity is seeking energetic engineers to join our highly driven Agent Engine team. The Agent Engine team designs and builds powerful agentic experiences including Perplexity Computer , the Comet ecosystem, our Agent API, and more. In short, we build frontier intelligence systems for the world's most discerning users. As an engineer on our Agent Engine team, you'll bring AI expertise, sharp product intuition, and a tinkerer's mindset to advance the frontier of what agents can accomplish for our millions of devoted users. You'll work across engineering and applied research to solve many open problems in AI, including: - Designing frontier agent harnesses and systems to perform high-stakes, mission-critical work for our users; - Leveraging action and decision models that determine, based on complex multimodal states, how to accomplish user-specified objectives; - Providing consistently excellent experiences across local execution, headless cloud, custom executors, and other environments through sound system design and flexible abstractions; - Developing permission architectures, payload classifiers, and other methods to implement secure-by-design agentic capabilities; - Designing optimal data representations and modes of interaction between agents and their environments; - and much, much more. Qualifications - Strong foundational familiarity with the AI systems stack. - Proficiency in Python (bonus points for TypeScript, Go, and/or Rust). - Significant experience in at least one of the following areas: - Harness engineering - Agent Skills and plugin architectures - Model training and reinforcement learning - Browser technologies (CDP, Playwright, extension development, etc.) - Strong technical intuition and taste for user experience excellence. - Comfortable working with a small, fast-moving team; bias toward ownership. - A passion for shipping products that surprise and delight.
Forward Deployed Engineer - ML (London)
About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you’ll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads: LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You’ll help teams reach outcomes most engineers can’t on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We’re looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. What You’ll Work On: - Work hands-on with companies like Suno, Cognition, and Meta to architect and optimize production AI workloads on Modal - Contribute to open-source projects (members of the team are active contributors to SGLang) and publish technical content that demonstrates Modal’s capabilities across the AI stack - Collaborate with Modal’s product and sales teams, contributing to the platform as both an engineer and a product stakeholder - Build trusted relationships with technical leaders (CTOs, VPs of Engineering, ML leads) at companies doing frontier AI work - Conduct technical demos, experiments, and proofs of concept that make Modal’s performance advantages tangible You May Be a Fit If: - You have 2+ years of professional ML engineering experience, ideally with hands-on work in inference optimization, model training, GPU programming, or ML infrastructure - You’re familiar with the serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains and can go deep on at least one (you don’t need all of them) - You’re a strong communicator who can go deep on technical architecture with an engineering team and clearly articulate tradeoffs to technical leadership - You have a genuine interest in working directly with customers: you find it energizing to understand someone else’s problem and help them solve it - You’re willing to work in person in London Nice-to-Have: - Side projects, open-source contributions, or published work you’re proud of in ML or systems performance
Forward Software Engineer, Data
About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About The Job As a Forward Software Engineer, Data, you will build the systems behind some of the hardest problems Mistral takes on. You join our team of engineers in Applied AI. We gravitate towards hard problems, decide how to solve them, and ship fast. You work closely with our customer-facing teams, and what works goes into production with our customers and across the company. When a project needs it, you work directly on customer engagements. We're looking for a strong software engineer who builds end to end and has shipped ML or GenAI systems to production. You've felt the pain of models that pass every eval and fail on real data, and of quality that drifts after launch. You've also felt the data engineering pain: pipelines that break silently, schemas that change under you, and backfills that take a weekend. Data engineering is your edge. You turn messy, large-scale data into systems that hold up. You think like a founder. You start from the customer's problem, not the technology. You measure success by the value you deliver, and you care about building experiences people love to use. You like working at the edge of what AI can do today, and you push past it. Your scope is end to end, from first prototype to production. Your depth in data architecture helps set the standard for how the team designs and delivers systems. You know lakehouse and data mesh patterns well enough to know when they fit and when they're overkill. You've designed ontologies and data models, and you know that getting them right is as much art as science. What you will do - Build AI systems end to end, from first prototype to production. - Design the data architecture underneath them: ingestion, processing, storage, and the data models and ontologies that make messy data usable. - Build distributed pipelines that process large volumes of documents, code, logs, and multimodal content for retrieval, agentic workflows, and fine-tuning. - Turn what works for one customer into patterns and platforms that work across many, without rebuilding each time. - Make systems hold up under real load: throughput, latency, cost, and failure recovery are part of the design from the start. - Build data governance into the systems themselves: ownership, access control, lineage, retention, and privacy for sensitive enterprise data. - Build the evaluation loop: labeling with LLMs and humans, versioned eval datasets, and checks that catch quality drift before customers do. - Set the standard for how the team designs and ships data systems. - Work with researchers, engineers, and customer-facing teams to turn hard problems into systems people rely on. What We're Looking For - You have full ability to ship across the stack: proficient NodeJS e.g. NextJS/Express/Fastify or similar or Python e.g. FastAPI. You are confident with TypeScript + React/NextJS or similar. Solid beats polished. - You have 5+ years of experience building and running production data-intensive pipelines with distributed processing (for example Spark, Ray, Beam, or Dask) and orchestration tools (for example Airflow, Dagster, or Prefect) with structured and unstructured data. - You have experience with retrieval-augmented generation, agentic use cases, or LLM evaluation, and a clear view of how data quality drives model quality. - You work autonomously: you find the problem, decide the approach, and own the outcome. - You communicate clearly with technical and non-technical audiences, and are fluent in English. - You ship in increments, are obsessed with time to value and are comfortable making and articulating product-technical tradeoffs. Ideally you have - A passion for graph-based systems (e.g. Neo4j) and ontology design - Hands-on experience building data pipelines for LLM training, fine-tuning, or evaluation, and contributions to open-source projects, particularly in data or LLMs. - Hands-on experience with data governance and privacy requirements (for example GDPR), secure data handling, CI/CD and infrastructure as code, or an affinity for security engineering. How We Work in Applied AI - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .
Field Execution Partner, AI Field Engineering
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 technical, field-tested operator to serve as the dedicated execution and enablement partner for our AI Field Engineering (AFE) team. As part of Revenue Operations, you'll design the programs and lead the change that keep this team sharp, consistent, and ahead of the curve as Fireworks scales. This role requires deep domain experience as a former AFE, Solutions Architect, or Sales Engineer. You'll pair technical credibility with business-operations rigor to bring a clear point of view on what great looks like and the program discipline to make changes stick globally. You'll also use your own AI fluency to bring agentic workflows into how AFEs work day to day. Your success will be measured in AFE outcomes: time to first technical win and ramp compliance for new hires, and productivity across the ramped team. Please Note: This is an individual contributor role reporting to the Head of GTM Enablement. Expect ~15–20% travel for team events and trainings. What You'll Own - Embed in AFE leadership and drive critical change management initiatives: Take a standing seat in AFE leadership forums, where you'll help shape the segment's go-to-market strategy alongside your RevOps counterpart. As the operating model evolves, you'll drive the execution of the team's most critical initiatives, whether that's a multi-quarter transformation or a fix shipped in days. - Design and deliver ongoing enablement programs for tenured AFEs: Keep experienced AFEs ahead of a fast-moving product with a continuous cadence of AFE-specific enablement, spanning technical trainings, process execution, skills workshops, and manager-led certifications. - Optimize the AFE ramp program and own the outcomes for new AFEs: Audit and continuously improve the AFE onboarding experience, from our Firecademy onboarding program through full ramp, and make sure every new AFE ramps consistently, wherever they sit. You'll be measured on time to first technical win, ramp compliance, and ramp productivity. - Surface and scale AFE best practices: Pinpoint what top AFEs do differently through call reviews, field conversations, and performance data. Then scale those patterns across the team with programs like peer showcases, POC reviews, and a curated call library, and feed what you learn back into the broader go-to-market team. - Build the AI tools AFEs use on live deals: Design and ship AI agents that work inside the AFE workflow, such as POC preparation, eval design, and technical objection handling, so AFEs move faster with customers. Minimum Qualifications - 8+ years of experience, including significant time as an AFE, Solutions Architect, Sales Engineer, or in a similar technical pre-sales role - Technical depth in AI/ML or developer infrastructure, and the credibility to coach technical sellers who work with technical buyers - A track record of driving change across a team, with the rigor to define, track, and act on the metrics that prove it worked - Strong at both content development and live facilitation for technical audiences, from new-hire cohorts to experienced practitioners - Has personally built AI agents or apps, through prompting, no-code, low-code, or code, to drive seller or operational productivity (engineering degree not required) - Thrives in ambiguity, high ownership, and the pace of a high-growth startup - Based in AMER and willing to travel ~15–20% Preferred Qualifications - Experience as a first- or second-line leader of a technical pre-sales team, or as Chief of Staff to a GTM leader - AFE, SA, or SE experience at an AI/ML infrastructure, developer tools, or API-first and consumption-based business, with literacy in usage-based pricing models - Prior ownership of onboarding, ramp, or enablement programs for technical sellers - Fluency in enterprise sales methodologies (e.g., Command of the Message, MEDDICC) applied to technical pre-sales - Familiarity with modern enablement tooling and systems (LMS, CMS, CRM, conversation intelligence) 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 Scientist, Discovery (Engineering & Appli...
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Discovery team at Anthropic is organized around the north star goal of building an AI scientist – a system capable of solving the long-term reasoning challenges and basic capabilities necessary to push the scientific and technological frontier. We're expanding our work on engineering and the applied sciences. Our goal is to contribute to training Claude to invent, design, and engineer across every discipline and scale, reliably and safely: new manufacturing and experimental techniques, processes, materials, devices, instruments, machines, energy systems, and factories. We want this work to accelerate science and technology and benefit people widely. To achieve these goals, we're seeking exceptional machine learning researchers with deep expertise in training and evaluating frontier models. In this role, you'll work end to end across the model stack, developing training environments, rewards, data, and evaluations that measure and improve Claude's performance on complex engineering and scientific tasks, and carrying what works into production training runs. You'll collaborate closely with researchers, engineers, and partners across Anthropic and industry to build AI systems that can engage in all phases of research and development, and that learn from real-world feedback. A background in engineering or the sciences is a plus but not required. Key responsibilities - Design, build, and study reinforcement learning environments, rewards, and training data that improve Claude's capabilities in engineering and the applied sciences - Create benchmarks and evaluation frameworks that measure model performance on realistic engineering and scientific workflows - Develop simulation-based training environments and verifiers, working with domain experts to validate them against real-world data - Develop approaches to long-horizon task completion, multi-agent collaboration, and complex reasoning essential for real engineering and research work - Research how models can learn efficiently from experiments and real-world feedback - Study how environments and rewards behave in large-scale training, including robustness, calibration, and generalization, so that training produces models that are both capable and well aligned - Scale research ideas from prototype to production training runs - Collaborate with domain experts and industry partners to build and test what Claude invents, designs, and engineers, and turn that feedback into training and evaluation signal - Help chart how Claude’s engineering capabilities reach real-world use: where they matter most, what stands in the way of adoption, and how that should shape research priorities Minimum qualifications - Proficiency in Python and hands-on experience with a modern machine learning framework such as PyTorch or JAX - Hands-on experience training or evaluating machine learning models - Track record of machine learning research: forming hypotheses, designing and running experiments, and drawing sound conclusions from the results - Ability to implement your own research ideas and diagnose problems in complex systems - Ability to learn unfamiliar technical fields quickly and work productively with experts in them - Clear communication and a collaborative approach to solving problems - Excitement about improving Claude’s scientific capabilities and the downstream impact on science and technology - Commitment to developing AI that is safe and beneficial Preferred qualifications - Experience with reinforcement learning and pre-training on large language models, including environment and reward design - Familiarity with large-scale language model training, evaluation, and inference pipelines - Published research or practical experience in AI for science or engineering, or in long-horizon reasoning - A degree or work experience in an engineering or applied science discipline, such as mechanical, electrical, materials, chemical, aerospace, systems, or manufacturing engineering, applied physics, or computational simulation - Experience building simulators, surrogate models, or simulation-based environments and verifiers, and calibrating and validating them against real-world data - Experience with large-scale data pipelines and technical or multimodal datasets - Demonstrated ability to work across multiple domains, such as language modeling, systems engineering, and scientific computing The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 - $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Research Engineer, Cybersecurity RL (Reinforcement...
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team The Security team protects Anthropic's AI systems and maintains the trust of our users and society. About the Role At Anthropic, we are pioneering new frontiers in AI that have the potential to greatly benefit society. However, developing advanced AI also comes with risks if not properly safeguarded. As a Research Engineer, you'll help to safely advance the capabilities of our models in incident response, security analysis, vulnerability remediation, and other areas of defensive cybersecurity. This role blends research and engineering, requiring you to both develop novel approaches and realize them in code. Your work will include designing and implementing RL environments, conducting experiments and evaluations, delivering your work into production training runs, and collaborating with other researchers, engineers, and cybersecurity specialists across and outside Anthropic. This role requires ML experience combined with domain expertise in cybersecurity. You might be an ML researcher with a history of cybersecurity work, or a security professional with a background in ML. Responsibilities - Partner with researchers and safety teams across Anthropic to understand their analytical needs and build solutions - Develop agentic integrations that allow AI systems to autonomously investigate and act on analytical findings - Contribute to the strategic direction of the team, including decisions about what to build, what to partner on, and where to invest - This role may require participation in an on-call rotation. You may be a good fit if you - Have experience with machine learning. - Have experience in cybersecurity research. - Have strong software engineering skills. - Can balance research exploration with engineering implementation. - Are passionate about AI's potential and committed to developing safe and beneficial systems. Strong candidates may also have - Professional experience in security engineering, fuzzing, detection and response, or other applied defensive work. - Experience participating in or building CTF competitions and cyber ranges. - Academic research experience in cybersecurity or other experimental & research background. - Familiarity with RL techniques and environments. - Familiarity with LLM training methodologies. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $1 - $2 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
AI Scientist Intern - (Internship, Masters or Phd)
About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers. Mistral AI are hiring experts in the role of pre-training and fine-tuning large language models. Role Summary -You will be working with the fine tuning team on making state-of-the-art generative models. -You will run autonomous work streams under the supervision of experienced scientists. -The role is based in one of our offices in Paris, London, Zurich or Warsaw. -Internship duration : 6 months. We will only consider candidates looking for end of studies internships (Master or Phd) What you will do -Explore state-of-the-art LLM algorithms for fine tuning LLMs, with the supervision of top level scientists. -Assist in the design and implementation of machine learning models and algorithms. -Conduct research on the latest advancements in natural language processing and LLMs. -Contribute to the development and optimization of our LLM systems. -Collaborate with cross-functional teams to integrate LLM technologies into various applications. -Perform data analysis and visualization to support research and development efforts. -Document research findings and contribute to technical reports and publications. -Participate in team meetings and brainstorming sessions to share ideas and insights About you -Currently doing a Master or PhD at a tier 1 engineering schools / Universities. -High scientific understanding of the field of generative AI. -Broad knowledge of the field of AI, and specific knowledge or interest in fine-tuning and using language models for applications. -Strong programming skills in Python, with experience in libraries such as TensorFlow, PyTorch, or similar. -Familiarity with natural language processing techniques and machine learning algorithms. -Design complex software and make them usable in production. -Navigate the full MLOps technical stack, with a focus on architecture development and model evaluation and usage. -Previous experience with LLMs or related technologies. -Knowledge of deep learning frameworks and techniques..Experience with version control systems (e.g., Git) and linux shell environment. Now, it would be ideal if you : -Have experience in fine tuning LLMs. -Have used complex HPC infrastructure with full autonomy. What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .
Partner Applied AI Engineer - LATAM
About the Team The Partner Applied AI Engineer team ensures the safe and effective deployment of Generative AI applications for developers and enterprises. We act as trusted advisors and technical partners to our customers, helping them build and execute their AI adoption strategy post-sale. Our mission is to develop a strong backlog of GenAI use cases tailored to each customer’s industry and to drive these initiatives from prototype to production through hands-on technical guidance and partnership. As a Partner Applied AI Engineer, you’ll support systems integrators and their most strategic customers transform their business through solutions such as customer service, automated content generation, and novel applications that make use of our newest, most exciting models. About the Role We are looking for a driven solutions leader with a product mindset as one og the the founding Partner AIE to own the technical engagement with our systems integrators (including GSIs, RSIs, and boutique SIs) and ensure their customers achieve tangible business value with GenAI. You will help partners identify high-value use cases and provide technical enablement through the implementation of AI solutions. Your efforts will accelerate partners’ time to unlock distribution and adoption, ensuring they deliver exceptional results for our joint customers while maintaining high-quality standards. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Head of Solutions Architecture. This role is based in São Paulo . We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Deeply embed with GSIs, RSIs, and boutique SIs as the technical lead, serving as their technical thought partner to ideate and build novel applications on our API for their customers. - Work with senior SI and customer stakeholders to identify the best applications of GenAI in their industry and to build/qualify a comprehensive backlog to support their AI roadmap. - Intervene directly to accelerate customer time to value through building hands-on prototypes and/or by delivering impactful strategic guidance. - Forge and manage relationships with SI and customer stakeholders to ensure the successful deployment and scale of their applications. - Codify solution packages and architectural patterns to accelerate time to deployment for customers and partners. - Lead technical support during partners' initial projects to ensure successful implementations and mentor their technical teams towards self-sufficiency in delivering OpenAI-powered solutions. - Scale the Partner Solutions Architect function by sharing knowledge, codifying best practices, contributing resources to our open-source repositories, and publishing resources to internal and external knowledge bases. - Validate, synthesize, and deliver high-signal feedback to the Product and Research teams. You might thrive in this role if you: - Have 8+ years of technical consulting (or equivalent) experience, managing C-level technical and business relationships with complex global organizations. - Have led complex technical projects and programs with many stakeholders, ideally within or through an SI. - Have industry experience in programming languages like Python or Javascript. - Have led complex implementations of Generative AI and/or traditional ML solutions. - Have built and/or delivered prototypes using the OpenAI API. - Are an effective presenter and communicator who can translate business and technical topics to all audiences, including senior leaders. - Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done. - Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 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. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Software Engineer, Staff: Applied AI, Science & En...
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications. Claude is getting good at research. Given a well-posed problem, it can read the literature, write and run simulations, analyze results, and iterate on a design across physics, materials, chemistry, and engineering. But most of the hardest problems in science and engineering aren't well-posed. They live inside companies and labs with their own data, tools, constraints, and experts, and progress depends on turning all of that into work a model can actually do and check. Our Applied AI, Science & Engineering team takes Claude to the scientists and engineers working on hard problems in energy, materials, hardware design, and other physical-world fields. We build the tools Claude needs to do real research and engineering work. Mostly that means software: the agent harnesses, integrations, evaluations, and working processes that turn a partner's problem into something Claude can make progress on and validate. We find real-world problems and test what we build through partner engagements, then feed our learnings back to our research and product teams. It's early, and the engineers who join now will shape how Claude gets applied to science and engineering. This is an engineering role first. You'll spend real time with domain experts, become the person who knows how to get Claude working in their field, and prototype quickly alongside them. Most of your time, though, goes into building and hardening the systems that make that work repeatable, not into writing recommendations or configuring someone else's product. A science or engineering background is a big plus, but what matters most is that you can earn the trust of expert researchers, turn a fuzzy problem into something concrete and checkable, and ship. Responsibilities - Build the agent harnesses and research loops that let Claude carry a problem from literature review through hypothesis generation, simulation, analysis, and design iteration - Connect scientific computing and simulation tools (finite element, CFD, electromagnetic, or molecular modeling codes, for example) so Claude can drive them reliably and at scale - Design and build evaluations that tell us whether Claude's work is actually right, and be honest about where it isn't - Sit with scientists and engineers at partner organizations to learn their problem, data, tools, and constraints, and turn open-ended questions into well-specified, verifiable tasks with clear success criteria - Prototype with partners, ship pilots into their workflows, and cut anything that doesn't move the problem forward - Turn what works in one engagement into shared tools, reusable components, and documented processes the next one can start from - Be the technical voice on how Claude performs on science and engineering work, explaining results, limits, and tradeoffs clearly to researchers, engineering leads, and non-technical stakeholders alike - Partner with our research and product teams to share where models fall short on science and engineering work, and help shape what comes next You may be a good fit if you - Have 8+ years of experience building software, with strong engineering fundamentals and comfort across the stack, from data pipelines to tooling to quick interfaces - Have built real systems with large language models, including agents, tool use, or evaluations - Have worked on technical problems in a science or engineering field, such as physics, materials, chemistry, or electrical or mechanical engineering - Have a track record of zero-to-one work in startup or startup-like environments\ - Can work directly with expert users, understand their workflows deeply, and still keep the focus on building the right system rather than the one first requested - Have good judgment about what can and can't be verified, and are comfortable saying a result isn't good enough yet - Bring high agency, pick up new domains quickly, and hold strong opinions loosely - Communicate clearly with researchers, engineers, and external partners, and care about the societal impacts of your work Strong candidates may also have - An advanced degree or research experience in a physical science or engineering field - Hands-on experience with scientific computing and simulation, numerical methods, or optimization - Experience in industrial R&D, a national lab, or a deep-tech company in areas like energy, materials, manufacturing, or hardware - Experience building alongside customers or technical partners, for example in forward-deployed, applied AI, or solutions engineering roles, ideally where you also owned the software that came out of it - Experience with ML research, RL environments, or evaluation design Candidates need not have - 100% of the skills listed above - Formal certifications or education credentials - Expertise in every scientific domain we work in - Direct machine learning or AI research experience Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 - $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
ML Infrastructure Engineer - New Grad
SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value. About the Team The ML Infrastructure team builds and operates the inference stack that serves SambaNova's models on our RDU accelerators. We cover request scheduling, caching, decoding techniques, public APIs, and the accuracy testing that every inference feature must pass before it ships. About the Role As a new grad ML Infrastructure Engineer, you'll write production Python for our inference serving stack, including our vLLM integration and public APIs. You'll help bring features like speculative decoding, prompt caching, and tool calling into production on the RDU, and add accuracy and regression tests that catch problems before customers do. Responsibilities - Implement inference features on the RDU such as speculative decoding, constrained decoding, tool calling, prompt caching, and long-context inference - Adapt vLLM and related serving frameworks to the RDU architecture - Build and maintain endpoints in the public inference API - Write accuracy verification and regression tests for inference features - Debug latency, throughput, and reliability issues in production services Required Qualifications - B.S. in Computer Science, Electrical Engineering, or related field - Strong programming skills in Python - Understanding of algorithms, data structures, concurrency, and systems design - Coursework or project experience in distributed systems or machine learning - Experience with LLM serving frameworks such as vLLM, SGLang, or TensorRT-LLM - Experience with inference techniques such as speculative decoding, KV caching, or continuous batching - Experience with PyTorch Preferred Qualifications - M.S. or Ph.D. in Computer Science, Electrical Engineering, or related field - Experience building or maintaining APIs or backend services - Internship or research experience in ML systems or backend infrastructure - Experience with disaggregated systems - prefill/decode - Open source project ownership or contributions Base Salary Range: Base Pay Range $131,200 - $196,800 USD Submission Guidelines Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified. EEO Policy SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. Benefits Summary for US-Based, Full-Time Employment Positions SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.
Member of Technical Staff (Machine Learning Engine...
Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack: the models, the agent harnesses, and the search infrastructure underneath. That gives us the freedom to develop new approaches across all three training models to use search more effectively, designing tools and execution environments around learned behavior, and improving retrieval to support how agents actually work. Responsibilities - Push search and agent quality forward through improvements to models, training data, tools, and system design. - Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion. - Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate effectively. - Design and build agent harnesses around the tools, context management, execution environments, and orchestration that support reliable work over many steps. - Improve retrieval and ranking models and the search interfaces agents use to find and assess information. - Build datasets, reward signals, and evaluations that expose meaningful failures and guide improvements. - Own experiments end to end, from a clear hypothesis to scalable training, deployment, and measurable gains in quality, latency, and cost. - Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring new capabilities into production. Qualifications - A strong track record of building and shipping ML systems, with deep experience in one or more of LLM post-training, reinforcement learning, search and retrieval, or agent systems. - Strong software engineering skills and the ability to work across model training, experimentation infrastructure, and production systems. - Experience designing rigorous evaluations, diagnosing failures, and translating experimental results into practical improvements. - Comfort with open-ended problems that require both research judgment and hands-on engineering. - A strong sense of ownership, curiosity, and the drive to carry an idea through to a working system. Nice to have - Experience with training models to use tools or complete tasks over many steps. - Multi-agent training, coordination, or evaluation. - Building agent harnesses, distributed training systems, or scalable inference infrastructure. - Large-scale retrieval, ranking, or recommendation systems.
Applied AI, Technical Lead, Forward Deployed AI En...
About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About The Job: Mistral AI is seeking a Technical Lead, Applied AI to drive the technical strategy, execution, and delivery of complex AI solutions for our enterprise customers. In this role, you will lead a project teams of Applied AI Engineers, ensuring the successful deployment of Mistral AI products and the development of high-impact, scalable AI use cases. You will act as the primary technical point of contact for our most strategic customers, guiding them through the entire lifecycle—from pre-sales to post-implementation—while collaborating closely with research, product, and engineering teams to shape the future of our offerings. As a Technical Lead, you will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral’s technological vision. What you will do - Deliver as an IC the critical lines of codes of our complex projects , you’ll be hands-on and de-risk the critical parts of our complex projects. You’ll stay deeply involved in coding, reviewing, and optimizing AI solutions. - Lead technical teams of Applied AI Engineers , providing mentorship, technical guidance, and best practices for deploying state-of-the-art GenAI applications across industries. - Lead technical discussions during pre-sales , translating customer requirements into actionable solutions and communicating Mistral’s technological advantages to diverse stakeholders. - Design and oversee the implementation of complex AI systems , including fine-tuning, RAG, agentic workflows, and custom LLM applications, ensuring alignment with Mistral’s product roadmap and open-source initiatives. - Drive innovation by identifying emerging trends in AI , evaluating new tools and methodologies, and championing best practices for fine-tuning, inference, and deployment. - Work closely with product managers, researchers, and engineers to ensure seamless integration of customer feedback into Mistral’s product development cycle. How We Work in Applied AI - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it. About you - You are fluent in English. - You hold a PhD or Master’s degree in AI, Machine Learning, Computer Science, or a related field. - You have 7/8+ years of experience in AI/ML, with at least 2+ years in a technical leadership role (e.g., Tech Lead, Engineering Manager, or Solutions Architect) focused on AI products or enterprise solutions. - You have a proven track record of leading teams to deliver complex AI projects, from prototyping to production, in industries such as tech, finance, healthcare, or industrial automation. - You possess deep expertise in fine-tuning LLMs, advanced RAG, agentic systems, and deploying NLP applications at scale. - You are proficient in Python, PyTorch , and modern AI frameworks (e.g., LangChain, Hugging Face). Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools is a plus. - You have strong software engineering skills , including API design, backend/full-stack development, and system architecture. - You excel in technical communication , with the ability to articulate complex concepts to both technical and non-technical audiences, including executives and engineers. - You thrive in fast-paced, collaborative environments and are passionate about mentoring and growing technical talent. Ideally, you have: - Contributed to open-source projects, particularly in the LLM or AI space. - Experience in customer-facing roles (e.g., Solutions Architect, Customer Engineer, or Technical Product Manager) with a focus on enterprise AI adoption. - A track record of driving technical strategy and influencing product direction based on customer needs and market opportunities. Why join us? You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you! What We Offer We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page . Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .
Member of Technical Staff, Traffic Infrastructure
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 a Member of Technical Staff on our Traffic Infrastructure team, you will own the traffic layer behind our generative AI platform: the proxies, load balancers, service mesh, and routing systems that move every request reliably across regions and cloud providers. This is a highly technical role that calls for depth in distributed systems, cloud networking, and infrastructure, along with the judgment to balance latency, cost, and operational simplicity. You will partner closely with ML, product, and platform teams, and help set the technical direction for the team. Key Responsibilities: - Architect and build scalable, fault-tolerant traffic and networking services, including ingress and egress, load balancing, routing, and quality-of-service controls. - Lead technical design discussions, mentor other engineers, and establish best practices for operating large-scale infrastructure. - Drive network optimization both inside and outside data centers, including cost reduction, performance tuning, and removing scaling bottlenecks. - Evaluate and integrate cloud-native and open-source technologies (e.g., Kubernetes, Envoy, Istio) to strengthen platform capabilities and reliability. - Own systems end to end, from design through deployment and observability, with an emphasis on high availability, disaster recovery, and operational excellence. - Develop and maintain comprehensive monitoring, alerting, logging, and tracing to give deep insight into system health and performance. Minimum Qualifications: - Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience). - 5+ years of experience building backend or network infrastructure in cloud environments (e.g., AWS, GCP, Azure). - Strong software development skills in languages such as Go, C++, Rust, Java, or Python. - Deep understanding of distributed systems and networking fundamentals, including performance optimization. - Full product lifecycle ownership, from design through implementation to production. Preferred Qualifications: - Master's or PhD in Computer Science or a related field. - Hands-on experience with traffic or edge engineering, service mesh, or cloud networking (e.g., Envoy, Istio, DPDK). - Deep Kubernetes experience, including ingress, network policy, and custom controllers. - Track record of improving performance, reliability, and cost-efficiency on high-throughput systems. - Experience leading projects across teams and coaching distributed engineers. 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.
Manager, Applied AI Architect
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a leader of Applied AI Solutions Architecture in Japan, you will drive the adoption of frontier AI by enabling the deployment of Anthropic’s products (Claude for Enterprise, Claude Code, and API) across Japanese enterprises and digital-first organizations. You’ll leverage your technical skills and consultative sales experience to drive positive AI transformation that addresses our customers’ business needs, meets their technical requirements, and provides a high degree of reliability and safety. You’ll lead and grow a Japan Applied AI team as Anthropic’s presence in the market continues to expand. Applied AI comprises Solutions Architects, Product Engineers, and Finetuning Engineers. Working alongside the existing Japan Applied AI leadership, you will scale processes and best practices for the region’s technical pre-sales engagements, help each team member achieve success, high productivity, and career growth, and represent Anthropic as a technical lead on some of its most important partnerships. In collaboration with the Sales, Product, and Engineering teams globally and locally, you’ll help enterprise partners incorporate leading-edge AI systems into their cutting-edge products and platforms. You will employ your excellent communication skills, in both Japanese and English, to explain and demonstrate complex solutions persuasively to technical and non-technical audiences alike. You will play a critical role in identifying opportunities to innovate and differentiate our AI systems, while maintaining our best-in-class safety standards. Responsibilities - Lead and grow a team of Applied AI professionals in Tokyo (Solutions Architects and Product Engineers), providing both technical guidance and career development - Set goals and reviews for your team, promoting growth and output - Partner with the existing Japan Applied AI leadership to align on team structure, coverage, and best practices - Work with a handful of the highest-value enterprise customers on their overall AI adoption strategies, focusing on pre-sales technical excellence including use case scoping, technical champion building, and POC execution - Partner closely with your aligned GTM leadership to understand customer requirements and co-build GTM strategies to drive adoption for Japanese enterprise customers and partners (including SIers and resellers) - Contribute to thought leadership through conference presentations, webinars, and technical content creation - Own the technical portions of pre-sales engagements, ensuring your team provides compelling demos and validates enterprise customer ROI from Anthropic products - Drive collaboration across cross-functional teams to influence and unify stakeholders at all levels of the organization, including navigating consensus-driven decision-making within Japanese enterprises - Travel regularly to customer sites for executive-level sessions, technical workshops, and building relationships - Establish a shared vision for creating solutions that enable beneficial and safe AI in technology products - Lead the vision, strategy, and execution of innovative solutions that leverage our latest models’ capabilities - Stay current with emerging AI/ML trends and the competitive landscape in the Japanese enterprise tech sector You may be a good fit if you have: - 7+ years of experience as a Solutions Architect, Sales Engineer, or similar pre-sales technical role - 3+ years of technical go-to-market management experience, specifically managing pre-sales teams - Native or business-level fluency in Japanese and professional proficiency in English - Experience working with Japanese enterprise customers and understanding local business culture and decision-making processes (e.g., ringi/nemawashi, multi-layer stakeholder alignment) - Experience with the unique technical requirements and technical procurement processes of Japanese enterprises, including working through SIers and channel partners - Deep technical proficiency with enterprise AI deployments, API integrations, and production LLM use cases - An organizational mindset and enjoyment of scaling teams in a fast-growing, evolving environment - Excellent communication, collaboration, and coaching abilities - Comfort with uncertain, ambiguous, and fast-moving environments typical of the tech industry - Strong executive presence and the ability to foster deep relationships with technical leaders and engineering teams - At least a high-level familiarity with the architecture and operation of large language models and/or ML in general - Experience with prompt engineering, LLM evaluation, and architecting AI-powered systems - The ability to make ambiguous problems clear and identify core principles that translate across scenarios - A passion for making powerful technology safe and societally beneficial - Creative thinking about the risks and benefits of new technologies, beyond past checklists and playbooks - An active interest in emerging research and industry trends - Understanding of developer tooling, SDKs, and technical integration patterns common in enterprise tech companies Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Principal Place and Route (PnR) Engineer
SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value. About the team The Place and Route team writes the software that maps dataflow graphs onto SambaNova’s Reconfigurable Dataflow Unit (RDU). Our tools partition each graph, place the pieces on the chip’s compute and memory units, and route the communication between them. The quality of that mapping sets the throughput of the compiled program, including large language model inference and training. We are looking to grow our team with highly motivated engineers who want to utilize advanced algorithms to solve challenging problems. About the Role You will develop and tune the partitioning, placement, and routing algorithms that map customer workloads onto the RDU. You will work with the compiler team, hardware architects, and performance engineers to model new hardware constraints and trace throughput gaps back to mapping decisions. Your changes will ship in production releases and show up in measured performance. Responsibilities - Develop partitioning, placement, and routing algorithms that meet hardware resource constraints and keep compile times practical - Tune PnR results for target workloads, including LLM inference at different batch sizes and concurrency levels - Model new hardware constraints and architecture features in our solvers and heuristics as the chip evolves - Analyze compiled output with performance engineers and trace throughput gaps back to mapping decisions - Build the infrastructure for prototyping, regression testing, and deployment of PnR changes - Work with the compiler and hardware teams to define interfaces and resource models Required Qualifications - M.S. or Ph.D. in Computer Science, Computer Engineering, or related field - 3+ years of experience developing optimization or graph algorithms in industry or research - Expert knowledge of graph algorithms, partitioning algorithms, combinatorial optimization, or MILP solvers - Strong proficiency in C/C++ - Familiarity with Python - Experience designing large, highly parallel, performance-sensitive systems - Ability to learn hardware architecture and apply it to improve performance - Experience solving NP-hard problems in practice with heuristics, approximation, or pruned exact methods Preferred Qualifications - Experience with place and route for FPGAs, CGRAs, or other spatial architectures - Experience with ML compilers such as MLIR, LLVM, TVM, or XLA - Experience with simulated annealing, constraint programming, or SAT/SMT solvers - Familiarity with LLM inference stacks such as vLLM and PyTorch - Publications at venues such as FPGA, DAC, ICCAD, or MLSys Base Salary Range: Base Pay Range $1 - $999,999 USD Submission Guidelines Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified. EEO Policy SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. Benefits Summary for US-Based, Full-Time Employment Positions SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.
Forward Deployed Engineer, Post-Training
About the role As a Forward Deployed Engineer (FDE) focused on Post-Training, you will be a hands-on technical partner to our most strategic customers: AI teams using fine-tuning and reinforcement learning to build differentiated models on open-source foundations. FDE does not replace our Solutions Architects. You will work alongside them as the deep-domain specialist in post-training, guiding customers through data strategy, algorithm selection, experiment design, and evaluation, and sizing the compute behind it. You’ll make sure we can deliver on our post-training POCs, drive adoption of our fine-tuning and RL platform, and turn customer goals into measurable gains in model quality. Your work directly affects customer success, company growth, and the hardening of our core platform. Responsibilities - Data Strategy: Help customers define and execute their data strategy for model post-training, diagnose data quality issues that limit model performance outcomes, and provide recommendations for data generation for post-training scale - Algorithm Selection: Recommend the right post-training approach for each use case - Experiment Design & Hyperparameter Tuning: Design well-controlled experiments and tracking methods; diagnose training instabilities, reward hacking, and regressions. - Evaluation: Build evaluation frameworks with customers, including task-specific benchmarks, LLM-as-judge pipelines, and held-out test sets. Make sure gains are reproducibly aligned with production success metrics. - Model Selection: Guide base model selection methodology ahead of post-training efforts and baseline quality evaluations to guide post-training objectives. Interest in self-directed research of newly released open source models, particularly as they relate to post-training. - RL Workload Sizing: Scope and size RL and fine-tuning workloads, partner with sales and capacity teams to shape deals and capacity forecasts. - Strategic Customer Alignment: Serve as the primary post-training technical point of contact for aligned strategic accounts. Lead technical execution from scoping to production and make sure we hit critical milestones. - Product & Research Feedback Loop: Shape our fine-tuning and RL product roadmap with insights from the field. Contribute code, recipes, and reference implementations where needed, and drive early adoption of new features and research with strategic logos. Requirements - Experience: 5+ years in a technical role in ML engineering, Applied AI, Forward Deployed Engineering, or Solutions Architect, with recent hands-on experience post-training LLMs. - Post-Training Depth: Expert-level, hands-on experience with fine-tuning and/or RL for LLMs, including SFT, LoRA, DPO, and RL (GRPO, PPO, etc).. - Experimental Rigor: Strong track record designing experiments, running ablations, and building evaluations that separate real improvement from noise. - Data Intuition: Proven ability to build and iterate on training datasets - Model Landscape Awareness: Broad knowledge of state-of-the-art open-source models and strong judgment on which base model to post-train for a given customer requirements - Coding Proficiency: Strong Python skills; comfortable working in production environments. - Experience leading complex, customer-facing technical projects , with exceptional project management and communication skills. Able to work in a highly X-functional environment. About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $270,000 - $300,000 OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Application Policy Please read each role carefully and apply to the position best suited to you. Candidates are limited to 6 applications within a 90-day period, and applications beyond that limit will be automatically rejected. You may apply to additional roles 90 days after your last application. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our Privacy Policy at https://www.together.ai/privacy
Manager, Applied AI Architecture, Enterprise Tech
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: As the manager of the Solutions Architect team within Applied AI Enterprise Tech at Anthropic, you will drive the adoption of frontier AI in partnership with the rest of the go to market organization. Our Enterprise Tech customers are some of the world's most sophisticated technology companies, deploying AI at the core of their products and operations.. You'll leverage your technical skills and consultative sales experience to drive positive AI transformation that addresses our customers' business needs, meets their technical requirements, and provides a high degree of reliability and safety. You will be responsible for leading and growing the pre-sales team that partners with account executives to help those companies understand and deploy Anthropic’s products, including Claude for Enterprise, Claude Code, and the API. This will include leveraging your technical skills and consultative sales experience to hire great people, establish processes for the team to scale, and represent Anthropic directly at strategic customer engagements. Responsibilities: - Hire, manage, and guide a team of pre-sales Solutions Architects by providing both technical guidance and career development. - Set goals for your team in collaboration with sales and other parts of the organization that establish baseline expectations for performance. - Act as a technical sponsor for high-value strategic customers and advise them on their overall AI adoption strategies or use case scoping and POC execution. - Partner closely with Enterprise Tech sales leadership to identify new strategies to drive adoption of Anthropic products across customer use cases. - Work with cross-functional teams like product and engineering to ensure Anthropic prioritizes customer feedback or resolves blockers to adoption. - Travel to customer sites or conferences for executive-level sessions, technical workshops, and relationship building. - Establish a shared vision for creating solutions that enable beneficial and safe AI in technology products. - Contribute to thought leadership through conference presentations, webinars, and technical content creation. - Stay current with emerging AI/ML trends and the competitive landscape. You may be a good fit if you: - 7+ years of experience as a Solutions Architect, Sales Engineer, or similar pre-sales technical role. - 3+ years of technical pre-sales management experience. - Have deep technical proficiency with enterprise AI use cases, API integrations, and LLM deployments. - Thrive in building and rapidly scaling teams and processes within ambiguous and fast-moving environments. - Have excellent communication, collaboration, and coaching abilities. - Strong executive presence and ability to foster deep relationships with technical leaders and engineering teams at leading enterprise technology companies. - Have at least a high level familiarity with the architecture and operation of LLMs. - Have a passion for making powerful technology safe and societally beneficial. - Stay up-to-date and informed by taking an active interest in emerging research and industry trends within AI. Strong candidates may have: - Enterprise pre-sales leadership at scale : 5+ years leading solution architect teams through hypergrowth (ideally 10 to 50+ people), with direct experience managing senior individual contributors and developing junior talent in complex enterprise software sales environments. - AI Technical Depth + Executive Engagement : Hands-on experience with AI platforms and enterprise integration patterns, combined with proven track record engaging C-level stakeholders in $10M+ technical evaluations and enterprise sales cycles. - Multi-Segment GTM Experience : Demonstrated success adapting technical approaches across customer segments (commercial to Fortune 100). The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $1 - $2 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Privacy Specialist
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 Senior Privacy Specialist to be our privacy presence in the UK and EU as Fireworks scales its European footprint. We've achieved ISO 27001, ISO 27701, ISO 42001, and SOC 2 Type II, and we operate active UK GDPR, EU GDPR, and CCPA programs. You'll be our senior privacy point of contact for the UK and EU - the person who fields supervisory authority correspondence and owns the operational processes that keep our UK GDPR, EU GDPR, and Data Protection Act 2018 obligations met. You'll report to our Privacy Lead and work as part of a small global privacy team, with real autonomy over the UK/EU side of the program. This is a hands-on senior individual contributor role, and an advisory one. You'll be the privacy judgment in the room for the UK and EU: the person engineers, sales, and legal come to before they ship, sign, or answer. Who this role is for We're building a privacy function that punches well above its headcount. That shapes who succeeds here: - You've operated and built under ambiguity. You're used to being the one who owns it, and you've built structures where none existed rather than inheriting someone else's. - You build systems, not queues. You've used AI tooling, automation platforms, scripting, or workflow engines to take manual privacy work off the table - and you're excited to do more of that utilizing cutting-edge technology. - You take a project and finish it. You don't need prescriptive instructions or hand-holding - you spot what's broken, scope it, own it until completion, and socialize it within the organization. - You take extreme ownership. When something in your area goes wrong, you own it, fix it, and make sure it can't happen the same way twice - without waiting to be asked and without pointing fingers. What you'll do - Act as our senior privacy point of contact for the UK and EU: first line for the ICO and EU supervisory authorities, handling regulator correspondence and inquiries with support from our Privacy Lead and Legal. - Be the standing privacy advisor for the region: guidance to product, engineering, GTM, and Legal on what UK/EU law permits, where the grey areas are, and what risk you're recommending we accept. - Own UK/EU data subject rights outcomes: statutory deadlines, scope and exemption decisions, edge cases, and the regional record. - Own cross-border transfer compliance: UK IDTA and Addendum, EU SCCs, adequacy analysis, and Transfer Impact Assessments for vendors, sub-processors, and intra-group flows. - Lead breach assessment and notification for UK/EU: triage, 72-hour notification decisions, regulator and data subject communications, and post-incident follow-through with Security and Legal. - Embed privacy-by-design into how we build: review new products, features, models, and vendors for privacy risk, and give engineering and product teams guidance they can act on. - Partner with our AI governance work on privacy in model training, fine-tuning, and inference - data minimization, purpose limitation, customer data handling, and emerging EU AI Act obligations. - Keep the UK/EU privacy notice and policy library accurate, practical, and aligned to what we actually do and our regulatory obligations. - Take on additional privacy projects as the program evolves; we're a growing team with dynamic priorities. How the role will grow As the program matures and our European footprint expands, you'll have the opportunity to: - Regional ownership - take on privacy for additional jurisdictions as we enter new markets, and shape our approach to emerging regimes. - Advisory reach - become the privacy voice in the highest-stakes decisions: new markets, new product categories, regulator engagement, and AI Act readiness. - Program ownership - take a hand in setting program direction, roadmap, and strategy. What we're looking for - 5-7 years of experience in privacy or data protection, with meaningful time in a tech, SaaS, or cloud company. - Deep, hands-on working knowledge of UK GDPR, EU GDPR, and the Data Protection Act 2018 - you've been a key player in a program complying with these regimes, not just worked on a small portion of one. - Experience as the sole or primary privacy owner for a region, product, or company; you're comfortable without a large team around you. - Track record running DPIAs and DSARs hands-on, and advising product and engineering teams on privacy-by-design. - Direct experience with international transfer mechanisms (UK IDTA, SCCs, adequacy, TIAs) and the judgment to apply them to real vendor and architecture decisions. - Some exposure to a supervisory authority - whether as a DPO, deputy, or otherwise. - Excellent communication; you work confidently across engineering, legal, sales, and executive audiences, and you can turn regulatory requirements into clear guidance. - Comfort with low-code automation and LLM-based tooling - enough to specify, evaluate, and get hands-on with the systems that run your program. - Based in the EU/UK with the right to work in those geographies. Nice to have - Privacy certifications (CIPP/E, CIPM, CIPT, FIP). - Experience with privacy tooling (OneTrust, TrustArc, Transcend, DataGrail, Securiti, or similar) - especially if you've pushed one past its out-of-the-box limits. - Exposure to ISO 42001, AI/ML data governance, model training data considerations, or the EU AI Act. - Experience standing up a privacy function in-region at a growth-stage company. 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.
Staff+ Software Engineer, VectorDB
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is looking for a Staff+ Software Engineer to work on the vector search infrastructure behind Claude. Retrieval is how Claude learns about the world. Web search across claude.ai, the API and agentic surfaces, memory across conversations, and the reinforcement learning workloads that train our next models all depend on fast, cheap, high-recall nearest-neighbor search over billions of vectors. You'll join a small team responsible for the vector database layer that serves Claude's retrieval workloads: its architecture, performance, scalability and cost. This is a foundational role. The team is small, core architectural decisions are still open, and the engineers who join now will shape how the system evolves. The role sits in our Databases organization and works day to day with the Search Platform team, which owns web search indexing, retrieval and serving, and the Memory & Search team, which owns search and memory inside claude.ai. We're looking for someone who has built vector or search systems that ran in production, at scale, with real users and a real on-call. You'll be hands-on in the code, and you'll also be the person deciding how the pieces fit together. Key responsibilities - Own the core of Anthropic's vector database layer: index structures, storage layout, query execution and the serving layer - Own production readiness - benchmarking against exact search, capacity planning, onboarding new workloads, and the operational tooling to run it at scale - Drive the recall, latency and cost trade-offs - quantization, filtered search, index build and refresh strategy, and how compute and storage are separated and scaled - Scale throughput by an order of magnitude as research and training demand grows, and work out whether the bottleneck is architecture, hardware or engineering bandwidth - Extend the retrieval stack toward hybrid retrieval - lexical search and fused ranking alongside vector search - Set the evaluation methodology for the system - recall targets, latency objectives, cost per query, and the regression detection that keeps them honest - Set technical direction for a growing team - lead design reviews, make architectural decisions others build on, and mentor the engineers joining the effort - Share the on-call for the systems you own Minimum qualifications - Direct experience building a vector database or approximate nearest-neighbor search system that ran in production at scale - Deep knowledge of ANN index structures (graph-based, clustering-based or disk-resident approaches), vector quantization and filtered search - Experience with search relevance and ranking - Strong systems programming skills in a language such as Rust, C++ or Go, including performance-critical and memory-intensive code - Experience designing and operating large-scale distributed storage or serving systems with strict latency and reliability requirements - A track record of independently scoping and delivering ambiguous, multi-quarter technical projects - Strong written and verbal communication, with experience driving alignment across teams with different priorities - Interest in AI safety and Anthropic's mission Preferred qualifications - Experience with object-storage-backed or disaggregated compute and storage database designs - Experience building or operating full-text search engines (inverted indexes, BM25) or hybrid retrieval systems - Familiarity with embedding models and the retrieval demands of LLM training and inference - Experience using GPUs or other accelerators for index build or search - Prior experience as a technical lead on a database or search infrastructure team The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 - $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Privacy Program Engineer
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 looking for a Privacy Program Engineer to own the technical core of our privacy program. We've achieved ISO 27001, ISO 27701, ISO 42001, and SOC 2 Type II, and we run active GDPR and CCPA/CPRA programs - now we need someone to run the machinery that keeps all of it working, and to make that machinery largely run itself. This is a privacy role with real technical depth - you'll write scripts, queries, and automation. From day one you'll own real workstreams: data subject requests, the data inventory and ROPA, hands-on privacy reviews for new vendors and features.. You'll report to our Privacy Lead and be a key owner of large portions of our privacy program, as well as the key technical expert on the privacy team. This is not a ticket queue with a title. We're a small team at a company that builds AI infrastructure, and we intend to leverage it - you'll own the direction and design of the technical systems, automations, and tools that help us meet our privacy obligations at Fireworks. Who this role is for - You build systems, not queues. You've used AI tooling, automation, scripting, or workflow platforms to eliminate manual privacy work. - You're technical enough to be dangerous. You read code to understand what a service actually does with data. You can query a database without asking for help. You've automated something real with code, a workflow engine, or an LLM-based agent and you know how to build scalable tools running against production systems and data. - You take a project and run with it. Given a rough problem and a deadline, you come back with it done. You’re not afraid to make tactical decisions and judgement calls. - You take extreme ownership. You're comfortable owning something outright and figuring it out - your workstreams are yours. You surface problems early, fix them, and make sure they don't recur. What you'll do - Build the privacy automation layer: scripts, scheduled jobs, API integrations, and LLM-based agents that handle request routing, evidence collection, assessment intake, and control monitoring. - Own the data subject rights (DSR) program and the system behind it: build the intake, identity verification, fan-out across data stores, and fulfillment tracking as an automated pipeline rather than a checklist, with the audit trail generated as a byproduct. - Build and maintain a data inventory and ROPA that derives from the environment rather than from interviews: pull from cloud APIs, warehouse metadata, IaC, and service catalogs so the map updates when the systems do, and reconcile drift. - Embed privacy into how we build: review designs and PRs for data handling, advise on de-identification, pseudonymization, tokenization, field-level encryption, and access scoping, and give engineers a concrete pattern to use rather than a policy to read. - Own retention and deletion as an engineering problem: translate retention requirements into concrete rules per data store, work with engineering on enforcement in pipelines and backups, and build the verification that proves deletion actually happened. - Support consent management and preference handling across our web properties and product surfaces. - Solve AI data problems directly: trace how customer data moves through training, fine-tuning, inference, and logging; validate zero-retention and isolation claims against what the platform actually does; and build the checks that keep those claims true as the platform changes. - Take on additional privacy projects as the program evolves; we're a growing team with dynamic priorities. How the role will grow - Process ownership - move from operating established processes to owning entire workstreams end to end. - Automation ownership - take the lead on privacy tooling and agent design as the program's automation surface grows. - Advisory depth - advise product and engineering teams directly on technical privacy-by-design decisions. - Growing influence - represent privacy in cross-functional projects, be the go-to technical privacy SME, and help shape where the program goes next. What we're looking for - 4–7 years of experience in privacy, GRC, IT audit, information security, or a closely related field, with meaningful hands-on privacy work. - Working knowledge of GDPR and CCPA/CPRA, and familiarity with ISO 27701, ISO 27001, ISO 42001, SOC 2, and NIST. - Hands-on experience with technical privacy operations: data subject requests, ROPA or data inventory maintenance, privacy impact assessments, or retention enforcement. - Evidence that you automate your own work - AI tooling, scripts, workflow builders, or aggressive use of a privacy/GRC platform's automation features. Tell us what you built and what it replaced. - Working proficiency in SQL and at least one scripting language - enough to query a warehouse, call an API, parse a schema, and automate a recurring task without help. - Hands-on familiarity with cloud environments (AWS, GCP, or Azure): IAM and access scoping, logging, data stores and their retention behavior, and how to find where data actually lives and how it’s used. - Strong written communication; you can translate privacy requirements into language engineers, customers, and non-technical employees understand. Nice to have - Built something with an LLM API or agent framework that other people relied on. - Experience with de-identification or synthetic data techniques. - Exposure to data lineage or catalog tooling (dbt, DataHub, Atlan, Monte Carlo, OpenMetadata). - Worked on a privacy or security problem at an AI/ML company specifically - model data flows, inference logging, training data provenance. - Startup or fast-growing SaaS background. 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.
Developer Advocate
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 This Role Developers decide what infrastructure wins. They try three platforms in an afternoon, keep the one that got them to a working inference call fastest, and tell everyone else about it. As a Developer Advocate at Fireworks, you own a piece of that decision: you make Fireworks the platform developers reach for first when they want to build, fine-tune, and serve frontier open models in production. You do that by building things worth showing, not by talking about things other people built. This role has a dual bar, and we mean both halves of it. You are a working engineer: you ship code, read diffs, deploy models, and can hold your own in a conversation about batching, quantization, or why a fine-tune regressed. You are also a public technical communicator: you write clearly enough that a senior engineer forwards it, you're good on a stage, and you have or want a real presence in the places developers actually argue about this stuff. Most people are strong at one and passable at the other. We're looking for the rarer profile who is genuinely credible at both, because in AI infrastructure the audience can tell within one paragraph whether you've actually run the thing. The field moves weekly. A major open-weights model drops and the window to be the definitive resource on it is measured in days. Your job is to be one step ahead of that cadence, consistently, and to make it look repeatable rather than heroic. This is one of the first advocate seats on the team, which means you'll help set the standards: for content, for launch response, and for how we show up. We're hiring at either the Senior or Staff level and will determine level through the interview process based on your experience. Location and Work Style This role is based in San Mateo, CA or London. You'll travel regularly to the conferences, hackathons, meetups, and partner events where the developer community shows up. Expect roughly 20% to 25% travel in a typical quarter, concentrated around major events and launches. If you're based in London, you'll anchor our presence in the European developer community, work across time zones with a primarily US-based team, and travel periodically to our San Mateo HQ for onsites and planning. What You'll Do Build things developers can run. Ship cookbooks, quickstarts, reference applications, and end-to-end tutorials that take a developer from zero to a working inference call and then to something production-shaped. Everything you publish is code someone can fork and run, not a screenshot of code that worked once on your machine. The bar is content a senior engineer respects and a new developer can follow, ideally both in the same artifact. Own the launch response. When a significant model or technique lands, you're among the first credible voices with a working demo, an honest benchmark, and a "how to actually use this today" guide. You'll help build the internal loop (model access, eval harnesses, publishing paths) that makes day-one content a process rather than an all-nighter. Show up where developers are, owned and unowned. On our properties, that's docs, blog, examples, cookbooks, Discord, and the developer newsletter. On properties we don't own, that's GitHub, X, Reddit, YouTube, Hacker News, and the open-source projects our developers depend on, including contributing code and reviewing PRs where it matters. You answer real questions in public and turn the recurring ones into permanent content. Speak, teach, and run the room. Conference talks, hands-on workshops, hackathon mentoring, and developer dinners. You'll help decide where Fireworks shows up and what we say when we get there, and you'll build the material so the next person can deliver it without starting over. Be the developer's voice inside Fireworks. Bring friction, feature gaps, and unmet needs back to product and engineering with evidence: a failing repro, a thread of five people hitting the same wall, a competitor's ergonomics that are simply better. Then close the loop publicly when we ship the fix. Measure what you do. You'll instrument your own work: what content drove signups, which events produced developers who actually built something, where people fall out between first call and production. We care about adoption, activation, and time to first successful build. We do not care about impressions, booth scans, or attendance counts, and we won't ask you to report them. What Success Looks Like in the First Year - You've published a body of technical work (tutorials, apps, deep dives) that developers cite and competitors read. - When a major model drops, Fireworks has authoritative, runnable content out fast enough to be part of the conversation rather than a follow-up to it. - You have a credible, recognized presence in developer communities where we weren't previously part of the discussion. - You've spoken at multiple significant events and left behind a workshop or talk that others on the team can now deliver. - Product and engineering can point to specific roadmap decisions that changed because of feedback you surfaced. - The content and launch standards you set are what new advocates onboard into, and they hold up without you in the room. What We're Looking For - 5+ years of combined engineering and developer-facing experience , with real time in both. For example, several years shipping production software plus meaningful time in DevRel, developer education, technical writing, or solutions engineering. We're flexible on the ratio and inflexible on the requirement that both are genuinely there. - You can code and read diffs. Strong Python; comfortable in TypeScript/JavaScript. You've built and deployed applications yourself, and you can review someone else's sample and tell whether it's good. - Hands-on with the modern AI stack. You've worked with LLM APIs in production, built with at least one agent framework, and have personally fine-tuned, evaluated, and deployed a model, not just read about it. You understand what inference latency, throughput, and cost actually depend on. - A public track record. Technical writing, talks, videos, open-source work, or a following you earned. Something we can go read or watch that shows you can explain hard things well to engineers. - Demonstrated speaking ability. You've presented at conferences, meetups, or workshops, and you're comfortable doing it on short notice about something that shipped last week. - Learning velocity. You can go from "this paper came out Tuesday" to "here's a working implementation and an honest assessment" quickly, and you have a system for staying current rather than relying on luck. - Ownership instinct. You pick your own topics, scope your own projects end to end, and don't need a content calendar handed to you. This role is early enough that you'll be defining the work as often as executing it. Bonus Points - Open-source contributions or maintainership in the AI/ML ecosystem, including inference engines, model libraries, agent frameworks, and evaluation tooling. - Depth in inference optimization, serving architecture, post-training, or evaluation methodology. - You've built something that outlived your direct involvement: a content operation, a launch process, an events playbook, or a community program. - Comfort making video. - Existing relationships with AI research or open-model communities. - You use frontier coding agents in your daily work and have opinions about where they help and where they don't. - Experience being early on a DevRel team and helping establish how it operates. 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.
Manager, Applied AI Cyber Specialists
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s mission is to ensure that the world safely makes the transition through transformative AI. Security is one of the clearest places where that mission plays out: the same capabilities that help attackers move faster can help defenders move faster too, and helping them use those capabilities safely and well is what this team is for. Security teams are among the earliest and most demanding users of frontier AI. They use Claude to review code at scale, find vulnerabilities before attackers do, and work through alert queues their analysts can’t keep up with. Anthropic’s Applied AI organization is building a dedicated Security team to help them do this well, and we are looking for its first leader. You will build this team from zero. You’ll decide which security customers the team serves first, who you hire and in what order, and how the team works with Sales, Applied AI Engineering, and our security, legal, and trust partners. You’ll also stay hands-on with a few of our most important security customers, because what you learn in those accounts becomes the playbook for everyone else. You’ll also set the standard for how security customers use Claude responsibly, including where a person has to review the output before anyone acts on it. What you’ll do - Hire, onboard, and develop the first Applied AI Architects on the Security team. Coach senior and early-career architects differently, and give each one clear goals. - Decide where the team spends its time: which segments and account types come first, which deals get architect coverage, and how to say no clearly when demand outruns headcount. - Partner with security account executives on joint account plans, regular pipeline and forecast reviews, and deals where the customer’s security review sets the close date. - Guide customers from discovery through evaluations and proofs of concept with written success criteria. Then take them from one-time code scans to sustained workloads: application security in the development lifecycle, continuous automated penetration testing, alert triage and investigation, and vulnerability and threat intelligence. - Work alongside the security ISVs, systems integrators, and managed security providers already in our customers’ accounts. Keep a clear line between what Anthropic delivers and what partners deliver. - Bring in Applied AI Engineers and our security, legal, and trust teams when a customer’s build or review needs them. - Write the first security playbooks, reference implementations, and evaluation approaches. Bring what you learn back to Product, Engineering, and Research, so Claude becomes more useful and more trustworthy for defenders at the same time. - Carry a small number of strategic security accounts yourself, from executive briefings with CISOs to hands-on workshops with their engineers. You may be a good fit if you - Have 12+ years of industry experience with at least 4 years managing a team of customer-facing technical people, such as solutions architects, sales engineers, or security consultants, and can show how the team grew and performed under you. - Have hands-on security depth in at least one area, such as application security, detection and response, offensive security, or vulnerability management, deep enough that practitioners trust your judgment . Application security experience highly preferred. - Have used LLMs for real security work, such as code review, vulnerability discovery, triage, or investigation, and can say where they helped and where they failed. - Have worked large enterprise security deals end to end, including customer security reviews, in close partnership with sales. - Care about making AI both safe and useful for defenders, and can explain security risk and value to a CISO and to the engineers who will run the work, in terms each one cares about. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $380,000 - $450,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Deployed Architect, Professional Services (London)
About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Role: We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. What You'll Do: - Infrastructure & Platform Engineering : Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development : Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment : Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams What You'll Bring: 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect, Deployed Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences Key Attributes: - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience Compensation: £100,000-£165,000 base salary + equity Location: - UK, London - Remote with up to 25% travel Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. Benefits Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
Technical Project Manager / Engineering Lead – AI/...
SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value. We are seeking a highly technical and strategic Project Manager / Engineering Lead to own and advance our engagement with a key strategic partner. The ideal candidate will be the central hub for all technical, operational, and strategic activities. You will be responsible for ensuring the technical success of joint projects, managing complex deliverables, leading a cross-functional engineering team, and deepening the customer relationship to secure future business. This role requires a unique blend of deep technical understanding of AI/ML systems, exceptional project management skills, and strong customer-facing abilities. Key Responsibilities - Technical Project Leadership & Execution: - Own the end-to-end planning and execution of complex technical evaluation projects ● Develop and maintain detailed project timelines, ensuring alignment between engineering efforts and customer milestones. - Lead daily standups and syncs to track progress, identify risks, and unblock the engineering team - Manage deliverables such as performance benchmarks, technical reports, and software artifacts. - Customer & Stakeholder Management: - Serve as the primary technical point of contact for the customer's engineering teams. - Manage customer expectations, clearly communicating project status, capabilities, and limitations. This includes being candid about software maturity and guiding the customer toward successful outcomes - Translate customer requirements and feedback into actionable engineering tasks. - Prepare and deliver technical briefings and reports to customer stakeholders at all levels. - Cross-Functional Team Coordination: - Coordinate the work of a large, distributed team of engineers specializing in compilers, performance SDKs, model bring-up, systems, and packaging. - Clearly assign action items and ensure accountability across different functional groups. ● Facilitate collaboration between internal teams (e.g., Product, Engineering, GTM) to ensure a unified strategy. - Technical Analysis & Strategy: - Understand and articulate the technical differentiators of the platform, such as scale-up/scale-out (SUSO) performance, compilation workflows, and comparative analysis against competitors - Drive technical decisions on project scope, such as selecting which models (e.g., Llama 70B/405B, Qwen, GLM) to focus on and defining the success criteria for deep engagements. - Analyze project outcomes to inform product roadmap and future sales strategies. Qualifications & Experience Required: - Fluent in Japanese and English. - Experience in supporting strategic Japanese and US high technical companies. Can manage cultural and time-zone differences. - 10+ years of experience in a technical project management, engineering lead, or customer-facing architect role within AI/ML, HPC, or systems infrastructure. - Proven experience managing complex software/hardware integration or evaluation projects with tight deadlines. - Strong understanding of AI/ML workloads, including model training, inference, and the associated software stack (e.g., PyTorch, vLLM). - Excellent communication skills, with the ability to explain highly technical concepts to both engineers and executive stakeholders. - Demonstrated ability to lead and influence cross-functional teams without direct authority. Highly Desirable: - Hands-on experience with large language models (LLMs) and mixture-of-experts (MoE) models. - Background in performance analysis and benchmarking of AI systems. - Familiarity with compiler technology, parallel programming, or high-speed networking. Success Metrics In the first 6-12 months, you will be successful if you: - Seamlessly take over the existing engagement and maintain strong customer satisfaction. - Successfully execute the next phase of technical projects, leading to a repeat purchase or expansion of the partnership. - Establish yourself as the trusted technical advisor for the customer. - Improve the efficiency and clarity of cross-functional team coordination. Base Salary Range: Base Pay Range ¥15,000,000 - ¥20,000,000 JPY Submission Guidelines Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified. EEO Policy SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. Benefits Summary for US-Based, Full-Time Employment Positions SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.
Research Intern, Frontier Speculative Decoding (Su...
About the Role The Speculative Decoding team at Together AI builds the draft models and algorithms that let large language models generate faster without changing their outputs. Our speculators run in production on frontier open models such as DeepSeek, Kimi and GLM. Our work sits at the intersection of model training, inference algorithms and serving systems, and we co-design all three to lower the cost and latency of generation. As a research intern, you will dive into open questions in speculative decoding: new drafter architectures and verification schemes, knowledge distillation and training recipes that align draft and target models, and drafters that adapt as traffic shifts. You will train and fine-tune draft models at scale on dedicated GPU clusters, and test your ideas against realistic serving workloads, including long-context and agentic traffic. Projects aim to answer important research questions in speculative decoding, enabling faster generation on frontier models, drafters that keep pace with changing workloads, and robust, reproducible evaluation under real traffic. Past Research Speculative decoding research by Together researchers, interns and academic collaborators includes: - Speculative Speculative Decoding (ICLR 2026) - When RL Meets Adaptive Speculative Training: A Unified Training-Serving System (ICML 2026) - Beat the Long Tail: Distribution-Aware Speculative Decoding for RL Training (MLSys 2026) Responsibilities - Research and prototype new efficient speculative decoding algorithms and draft model architectures - Train, fine-tune and distill draft models, and design rigorous experiments to validate hypotheses. - Implement optimized version for serving engines to show efficacy in real world workloads - Communicate the plans, progress, and results of projects to the broader team - Share findings through technical write-ups and blog posts, and help bring successful ideas into production Requirements - Currently pursuing a Master's or Ph.D. degree in Computer Science, Electrical Engineering, or a related field - Strong knowledge of Machine Learning and Deep Learning fundamentals - Hands-on experience training or fine-tuning large models with distributed training frameworks (e.g., Megatron-LM, FSDP) - Familiarity with modern model architectures, such as Mixture-of-Experts and hybrid attention Preferred Qualifications - Prior research experience in speculative decoding, efficient inference, or efficient machine learning - Publications at leading conferences in machine learning or systems (e.g., NeurIPS, ICML, ICLR, MLSys) - Experience with knowledge distillation, post-training, or reinforcement learning - Familiarity with LLM serving engines (e.g., vLLM, SGLang, TensorRT-LLM) - Contributions to open-source machine learning projects About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Internship Program Details Our internship program runs 12 to 14 weeks, giving you the opportunity to work alongside industry-leading engineers and researchers across multiple teams. This cohort's internship dates span May 17th to August 6th or June 14th to September 3rd. Compensation We offer competitive compensation, housing stipends, and other competitive benefits. The estimated US hourly rate for this role is $58 - $70 an hour. Our hourly rates are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Application Policy Please read each role carefully and apply to the position best suited to you. Candidates are limited to 6 applications within a 90-day period, and applications beyond that limit will be automatically rejected. You may apply to additional roles 90 days after your last application. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. For more information about our privacy policy, please visit: https://www.together.ai/privacy
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