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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 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 Engineer to join our Beneficial Deployments, Life Sciences team. Our goal is for Claude to close the loop on scientific discovery, and a significant part of this is helping Claude to drive scientific hardware and software. You'll help deploy the Model Hardware Standard (MHS) to labs doing the world’s most important research. You’ll scale what you learn in the field by contributing back to the standard, building scalable assets, and driving associated internal product and research direction. Responsibilities - Work with labs to automate their experiments end-to-end with Claude - from advising, to prototyping, to writing production code. - Drive product, engineering and research direction based on field experience - e.g. building evals to measure limitations of our models in the physical world (capabilities and safety), developing new features on MHS, etc. - Scale your impact to the long tail of labs through reusable cookbooks, documentation, and other assets. - Be an EMEA ambassador for Claude in the lab - you’ll both inspire and build trust with scientific audiences, from small settings to large conferences. - This role will require significant travel You Might Be a Good Fit If You Have - Hands-on experience connecting software to lab robots and instruments (liquid handlers, plate readers, scheduling software, LIMS), ideally in an automated lab. - Strong engineering skills: you can take an LLM-powered tool from prototype to production code, and write evals to measure its performance. - A scientist's instinct for how experiments work: you can spot what's worth automating, and where AI might fail or be unsafe in the physical world. - Experience working directly with external customers or partners in a technical role. - Clear written and verbal communication: you’ll write docs other labs can use without you and give talks that inspire and earn researchers' trust. - A scrappy mentality–comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission. 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: £225,000 - £255,000 GBP Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

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 We are seeking an experienced Engineering Leader to build the partnership engineering organization. In this role, you will lead and build a new team dedicated to the technically complex work we do with our Partners, turning that work into repeatable product features. You’ll work to scale the team as they grow, help prioritize and support work in a fast paced environment, and build a healthy team culture. This is a highly visible role with the opportunity to shape how Mistral’s technology is adopted globally and unlock large business opportunities What You Will Do - Remove obstacles and create an environment where your team can focus on building solutions. - Own the most critical partnerships of the company and what's required to make them a success. - Translate product vision into technical reality, collaborating closely with the Product team. - Ensure applications are performant, stable, and responsive. - Uphold high code quality standards through reviews, testing, and automation. - Own the full software development process, from design to deployment. - Plan projects, including roadmaps, deadlines, and task allocation. - Collaborate with stakeholders across Engineering, Product, and Design, and Partners. - Support team growth through hiring, onboarding, and mentorship. What We're Looking For - Experience building and managing engineering teams. - Proficiency in Python and at least one web framework (FastAPI, Django, Flask). - Proficiency in C#, Golang, TypeScript and at least one web framework. - Experience with large-scale distributed systems. - Experience working with cross-functional teams, such as Product, Design, and Business. - Strong problem-solving abilities and attention to detail. - Ownership mindset and ability to ship products end-to-end. - Excellent communication skills and a low-ego, team-first attitude. 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 .

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 Mistral AI is seeking Applied Scientists and Research Engineers focused on formal methods. You will design, train, and deploy SOTA large language models and apply them to diverse use cases. You'll work cross-functionally with internal and external science, engineering, and product teams to deliver high-impact AI solutions. What You Will Do - Run pre-training, post-training and deploy state of the art models on large clusters. - Generate and curate datasets for theorem proving and software verification, and build evaluators and benchmarks for formal reasoning. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases. - Manage research projects and communications with client research teams. What We're Looking For - Fluent in English with excellent communication skills — at ease explaining complex technical concepts to both technical and non-technical audiences. - Expert with PyTorch or JAX. - Not afraid of contributing to a big codebase; finds their way around independently with little guidance. - Writes clean, readable, high-performance, fault-tolerant Python code. - Doesn’t need roadmaps: moves independently and navigates uncertainty with confidence. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. Nice to have - PhD / Master in a relevant field (Computer Science, Mathematics, Machine Learning). - Experience with autoformalization, proof automation, or verified code generation. - Experience with reinforcement learning using verifiable rewards, ideally from Lean or other proof assistants. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. 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 .

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 Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. Key Responsibilities - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. Requirements - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. Nice to Have - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers , or TRL. - Experience with trace mining to drive continuous improvement loops Location San Francisco, CA Compensation $150,000-$300,000 base + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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.

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 Role We are hiring an LLM Scientist to push the boundaries of AI-driven scientific discovery. You will specialize in developing and optimizing large language models (LLMs), agentic AI, and deep learning frameworks to solve open problems in the natural sciences: Biology, Chemistry, Physics, and/or Materials Science. Your work will empower scientists with cutting-edge AI tools and accelerate research through: - Model-centric innovation : Improving LLMs’ capabilities to tackle complex scientific problems (e.g., literature synthesis, autonomous experimentation, rigorous derivations). - Cross-disciplinary collaboration : Partnering with Natural sciences domain experts to translate AI advancements into real-world scientific impact. What you will do - AI/ML Research : Participate in end-to-end training of LLM-based solutions, with a focus on scalability, generalization, and scientific applicability . - Data creation : Design original workflows to accumulate high quality scientific data at scale, either through synthetic or crowd sourced pipelines. - Algorithm Design : Use and improve reinforcement learning, or agentic systems tailored to Natural sciences challenges (e.g., modeling resolution, material property prediction, advanced data analysis and coding). - Interdisciplinary Bridge : Work closely with domain scientists to identify AI opportunities and refine models based on feedback. - Tooling & Infrastructure : Contribute to company infrastructure to improve usability for model training in scientific contexts and open-source AI tools for science for non-AI experts. - Autonomous Innovation : Set a research agenda for AI in science, exploring high-risk/high-reward ideas. What We're Are Looking For - AI/ML Expertise : Strong background in LLMs, deep learning, or agentic AI , with a track record of applying these to real-world problems (publications, open-source contributions, or deployed systems) – at the minimum extensive experience in computer science and ideally experience scaling synthetic data generation. - State-of-the-art Knowledge : Familiarity with the latest advancements in LLM architectures and post training. - Technical Depth : Hands-on experience with PyTorch/TensorFlow/JAX , model optimization, and scaling techniques (e.g., fine-tuning, RLHF). - Scientific Capability : Ability to understand 1 Natural Science domain at a high level (e.g., graduate level specialization + general undergrad knowledge) to design effective AI solutions. - Engineering Rigor : Proficiency in scientific computing (e.g., numerical methods, HPC) and software best practices. - Collaboration : Experience translating technical AI concepts for non-experts (e.g., scientists, engineers) and iterating based on user needs. - Mindset : Low ego, team player, and eager to tackle operational challenges (e.g., data pipelines, model deployment). Motivational paragraph When applying for the AI for Science team at Mistral, please describe in a short paragraph a potential project that you would like to contribute to the team, why it is challenging and interesting in general, and more specifically for Mistral. Please also highlight the specific skill set that you can bring to the team. 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 .

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 Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. Key Responsibilities - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. Requirements - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. Nice to Have - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers , or TRL. - Experience with trace mining to drive continuous improvement loops Location Remote Compensation $150,000-$270,000 base + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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.

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. For software engineering organizations, this means helping customers adopt Codex and other OpenAI capabilities across the software development lifecycle—transforming how teams plan, build, test, review, and deliver software. We work directly with engineering leaders and hands-on developers to identify high-value opportunities, design and implement AI-powered development workflows, and scale what works across engineering organizations. We turn lessons from these deployments into better products, reusable architectures, and technical patterns that help developers everywhere get more value from Codex. About the Role As an Applied AI Engineer focused on Codex, you will partner directly with leading engineering organizations to design, build, and deploy AI systems that transform how software is developed. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from workflow and use-case selection through prototyping, evaluation, production rollout, and scaled adoption. You will work alongside engineering teams to build advanced AI coding workflows, integrations, automations, and evaluation systems—often using Codex itself as part of your development process. You will help customers make technical decisions involving model behavior, agentic workflows, developer environments, security, reliability, evaluation, and operational readiness, while ensuring deployments translate into measurable improvements in engineering productivity and software delivery. You will work closely with OpenAI Product, Research, Engineering, Security, Sales, and the broader Codex organization, translating real-world deployment experience into high-signal product and model feedback. Success is measured by production systems, sustained developer adoption, and meaningful improvements to how engineering organizations build software—not simply successful demonstrations or enablement activity. This role is based in our Madrid office. 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 engineering leaders and hands-on developers to identify high-value opportunities for Codex and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. - Design, build, and deploy AI-powered software development workflows that improve how engineering teams plan, write, test, review, debug, and deliver software. - Work hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, workflow automations, and production accelerators—often using Codex as part of your own development process. - Help customers progress from promising experiments to reliable production workflows, sustained developer adoption, and scaled impact across engineering organizations. - Design systematic approaches for evaluating AI coding systems using representative software engineering tasks, automated graders, production signals, and developer feedback. - Make sound technical decisions across models, agents, tools, developer environments, integrations, reliability, observability, latency, cost, safety, security, and operational readiness. - Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive technical blockers toward resolution. - Lead technical deep dives, workshops, and hands-on enablement that help engineering teams understand and adopt advanced AI coding workflows effectively and safely. - Gather high-fidelity insights from real-world Codex deployments and translate them into clear product proposals, model feedback, and technical requirements for OpenAI Product, Research, and Engineering teams. - Create reusable architectures, tooling, examples, guides, and technical patterns—including contributions to resources such as the OpenAI Cookbook—that accelerate future Codex deployments. - Influence customer engineering strategy by helping technical leaders understand how AI coding systems can reshape their software development lifecycle, engineering practices, and organizational workflows. You’ll thrive in this role if you: - Have a demonstrated track record of designing, building, and delivering software or AI 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, developer tooling, customer engineering, solutions architecture, or technical consulting. - Can point to substantial personal contributions in code, architecture, evaluation, debugging, integrations, or production engineering—not only program, enablement, or stakeholder management. - Are highly proficient in Python and comfortable working across modern software development environments; experience with JavaScript, TypeScript, or another relevant language is valuable. - Are an active user of AI coding tools and have developed a strong point of view on how AI can improve developer productivity and software engineering workflows. - Enjoy building high-signal prototypes, integrations, automations, and production solutions that demonstrate and deliver what AI coding systems can enable. - Understand how to evaluate AI coding systems systematically, including designing representative tasks, automated evaluations, production signals, and mechanisms for incorporating developer feedback. - Have navigated enterprise production requirements such as developer tooling integrations, reliability, observability, security, privacy, data governance, performance, and cost. - Can connect technical decisions to developer workflows, adoption, engineering productivity, and measurable business outcomes. - Communicate with clarity and credibility across hands-on engineers, engineering leaders, security teams, product leaders, and executives. - Are comfortable leading technical workshops and hands-on sessions that help engineering organizations adopt new development workflows and technologies. - Bring high agency, strong technical judgment, and end-to-end ownership in ambiguous and rapidly evolving environments. - Learn quickly, challenge assumptions constructively, and collaborate with humility; deep prior experience with OpenAI products is not required. - Are able to speak English and Spanish fluently. 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.

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. Production-ready 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 Munich. 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 and digital native 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 might 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, product engineering or technical consulting. - Are fluent in both German and English - Can point to substantial personal contributions in code, architecture, evaluation, debugging, or engineering of production systems—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.

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 Applied Scientists and Research Engineers focused on time series. You will design, train, and deploy state-of-the-art time-series foundation models, and apply them to the most demanding forecasting problems in industry, from power grids and plants to trading desks. Timestral, our family of time-series foundation models, ranked first on amongst all benchmarks at release ( tech report : https://arxiv.org/pdf/2610.37585v1 ). The role has two sides: building the next generations of Timestral with our Science team, and taking them into production with our industrial and financial clients, adapted to their data. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions. We are made of researchers, engineers, product builders, ex-founders who love tackling the most complex real world problems in the industry. What you will do - Run pre-training, post-training and deploy state of the art time-series foundation models on clusters with thousands of GPUs. - Generate and curate large-scale time-series datasets, real and synthetic, and build evaluators and benchmarks for forecasting and other time-series tasks. - Push the frontier of Timestral: architectures, training recipes, scaling, and new capabilities such as anomaly detection, classification and embeddings. - Fine-tune and adapt Timestral on client data, in the cloud or on-premise, and benchmark it against the client's existing models. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases, including agents that combine Timestral with Mistral LLMs. - Manage research projects and communications with client research teams. About you - Fluent in English with excellent communication skills, at ease explaining complex technical concepts to both technical and non-technical audiences. - Expert with PyTorch or JAX. - Solid knowledge of modern deep learning and large language models: architectures, pre-training, post-training and evaluation. - Experience pre-training or fine-tuning time-series foundation models or large transformer models at scale. - Strong background in time-series modelling: probabilistic forecasting, multivariate series and covariates, and classical baselines (statistical models, gradient boosting). - Not afraid of contributing to a big codebase; finds their way around independently with little guidance. - Writes clean, readable, high-performance, fault-tolerant Python code. - Doesn't need roadmaps: moves independently and is comfortable with uncertainty. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. Nice to have - Ex-founder or builder - PhD / Master in a relevant field (Machine Learning, Statistics, Applied Mathematics, Physics). Exceptional candidates from other backgrounds welcome. - Research on time-series foundation models: pre-training, scaling, synthetic data or evaluation. - Hands-on experience training or fine-tuning LLMs, building agents and tool use, or models that combine text and time series. - Industry experience in energy, industrial operations, telecom or finance, or experience deploying models for industrial clients. - Experience working on large code bases or large machine learning models at scale. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. 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 .

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 leader of our Enterprise Asset & Wealth Management sales organization, you will build and lead a team that brings transformational AI to the world's leading asset managers, wealth managers, and private markets firms. These are organizations rethinking how they generate investment insight, serve clients and advisors, scale personalization, and meet fiduciary and regulatory obligations. They are looking for a partner they trust to take frontier AI from promising pilots into production at the core of their business. You will own a broad portfolio of major AWM institutions at very different stages of AI adoption, from firms already running Claude in production to those just beginning their journey. Your coverage will span global and regional asset managers, alternatives managers, and wealth businesses. You will lead Account Executives, design the coverage and territory model, and build the repeatable, AWM-specific plays that turn early wins into durable, scaled adoption across research, portfolio and client operations, advisor productivity, and compliance and supervision. The selling is technical and multi-stakeholder: platform decisions, model governance, security and procurement rigor, and solutions built on Claude through our API, Claude for Enterprise, Claude Code, and partner cloud platforms. You will shape strategy and operating rhythm while staying personally engaged with executives on the pursuits that matter most. This is a rare opportunity to build an organization, not just run a number: to shape how the asset and wealth management industry adopts frontier AI, and to do it at a company where safety, trust, and long-term customer outcomes are central to how we sell. Key responsibilities - Define AWM go-to-market strategy and coverage design, including segmentation across asset managers, alternatives managers, and wealth platforms, territories, account prioritization, and vertical value propositions, and evolve the coverage model as the business scales - Recruit, coach, and retain Enterprise Account Executives with deep asset and wealth management and platform-selling expertise; develop leadership talent and create career paths that keep top performers growing - Codify the use cases, proof points, reference stories, and sales motions that make wins repeatable across AWM, such as investment research and idea generation, portfolio and client reporting, RFP and due diligence automation, advisor productivity and client personalization, and compliance and supervision workflows, partnering with Marketing, Enablement, and partner teams to scale them - Engage personally with C-level and business-line executives (CEOs, CIOs, COOs, Chief Data and AI Officers, Heads of Distribution, and Heads of Wealth) on priority pursuits, building business cases and value narratives and navigating complex procurement, security, model-risk, and legal processes through to production deployment and expansion - Own the organization's revenue targets and operating rhythm, instilling pipeline-generation discipline and running forecasting, deal inspection, and account planning cadences that make performance predictable and coachable across a high-volume book of business - Partner closely with Applied AI, Solutions Architecture, and Product to design solutions, prove value quickly, and translate AWM needs, including fiduciary, books-and-records, and client-data requirements, into product and roadmap input - Orchestrate cross-functional and partner motions with Customer Success, Marketing, Partnerships, Legal, cloud partners, and the data and technology providers that AWM firms rely on, to deliver a seamless customer experience, and represent Anthropic with customers and at industry events as a visible, trusted leader Minimum qualifications - Experience leading enterprise sales teams that sell technical, complex products such as API-first platforms, cloud infrastructure, or data and machine learning platforms - A track record of winning and growing enterprise customers, including building C-suite relationships, in asset and wealth management (asset managers, alternatives managers, private banks, wealth platforms, or the technology and data providers that serve them) - Experience designing go-to-market coverage for an enterprise sales team, including segmentation, territories, and account prioritization - Operational rigor across both a high-volume pipeline and complex, multi-stakeholder sales cycles, balancing velocity with deal quality and forecasting accurately in fast-changing environments - Credibility with technical buyers and builders, and with investment and distribution leaders: CIOs, CTOs, CDOs, Heads of AI/ML, Heads of Research, and Heads of Wealth or Distribution, plus experience pairing effectively with solutions architects and applied AI teams - Strong coaching skills that raise team performance through deal coaching and account strategy, combined with personal effectiveness alongside executives on high-priority opportunities - A genuine interest in deploying AI responsibly and motivation to advance Anthropic's mission of building safe, beneficial AI Preferred qualifications - Experience leading other sales leaders (second-line management), or demonstrated readiness to step into that scope - Experience building or meaningfully scaling a verticalized or multi-segment sales organization - Experience bringing generative AI or LLM-based products, or other emerging platform technologies, to large asset managers, wealth managers, or private markets firms - Familiarity with AWM use cases and buyers, such as investment research and portfolio analytics, client reporting and RFP automation, advisor and relationship-manager productivity, and fund operations and servicing - Deep familiarity with regulated-industry selling in AWM, including fiduciary and suitability obligations, SEC and FINRA expectations on supervision and books and records, model-risk management, client-data privacy, security review, and the governance expectations of financial institutions - Experience selling with and through cloud and ecosystem partners such as AWS, Google Cloud, and global systems integrators, as well as the data, analytics, and portfolio-technology vendors embedded in AWM firms - Familiarity with consumption- or usage-based commercial models and value-based pricing conversations - Experience leading organizations through rapid growth, re-segmentation, or significant change 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: $450,000 - $700,000 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.

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 a Research Engineer on the Latency & Throughput team, you will push the frontier of LLM inference by researching and prototyping techniques that reduce latency and increase throughput — from speculative decoding and quantization to KV compression and new attention variants. The team sits at the intersection of research and production: you will take ideas from recent literature, form hypotheses, run experiments, and ship the techniques that prove out into our serving stack. This role sits between our inference engineers, who own the production serving stack, and our research scientists, who focus on paper-level contributions. You will be more science-focused than a pure engineer: you are expected to generate new ideas, keep up with the state of the art, and implement proof-of-concepts that bridge the gap between academic results and production impact. Some techniques you explore will be lossy or require integration into training — retraining models, tuning architectures, or training auxiliary models to improve inference. You will work closely with the Inference Foundation and Kernels teams, who turn your validated techniques into production recipes, and with pretraining and RL teams when your work touches model training. Success is measured by demonstrated latency or throughput gains, first at small scale, then adopted in production. What You Will Do - Research and prototype inference techniques — speculative decoding, quantization, KV compression, watermarking, and new model architectures — by reading recent literature and forming testable hypotheses. - Design and run experiments to validate or refute ideas, iterating quickly on small-scale setups before proposing production integration. Demonstrate clear latency or throughput gains without unacceptable quality loss. - Collaborate with the Inference Foundation team to integrate validated techniques into the vLLM-based serving stack. - Partner with pretraining and RL teams when techniques require co-training, retraining, or training auxiliary models to improve inference. Build the right tooling and validation platforms to facilitate AI-driven inference research. What We're Looking For - A strong ML background with solid knowledge of LLM training techniques — architecture, tokenization, fine-tuning, and evaluation. - Hands-on experience with Python and PyTorch; you write clean, experimental code and iterate fast. JAX is acceptable with strong Python proficiency. C++ and Rust are not required, CUDA and GPU knowledge is expected but hands-on experience is not required. - Research experience of some form: a thesis, publications, a dedicated research project, or efficiency-oriented work in a lab or industry research setting. A PhD is not required, but we are looking for genuine research depth. - A track record of conducting experiments: forming hypotheses, designing controlled comparisons, and drawing clear conclusions from results. - Familiarity with the state of the art in LLM inference — you know what has been tried, what works, and where the open problems are. - Self-starter, low-ego, and collaborative. You are comfortable with ambiguity, negative results, and are eager to take matters into your own hands. - Inference or serving experience is a plus, not a requirement. Prior work with vLLM, production LLM deployments, or serving systems will help you ramp up faster. Location and Remote This role is based in our Paris or London offices (hybrid). We will prioritize candidates who reside in the Paris area or are open to relocating. We strongly believe in the value of in-person collaboration to foster strong relationships and seamless communication within our team. For senior profiles, we will also consider remote candidates based in France. In that case, we ask all new hires to visit our Paris office: - For the first week of their onboarding (accommodation and travel covered) - Then at least 3 days per month 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 .

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 Role As a Research Engineer, GPU performance , you will sit at the heart of that spectrum: your low-level work directly determines how fast our frontier models can be trained and served. Working hand-in-hand with Research Scientists, you'll make every GPU count. Mistral AI is hiring an expert in pushing large language model's GPU utilization and performance to their limits.. In this role, you will own the performance of our models end-to-end: writing the low-level code that extracts the maximum capacity from high-end hardware, and rethinking model architectures so they run efficiently at scale. What You Will Do - Develop low-level code that takes full advantage of high-end GPUs and maxes out their capacity — from custom kernels to memory-layout and communication optimisations. - Rethink parts of the generative model architecture to make them more suitable for efficient inference, in collaboration with Research Scientists. - Integrate low-level efficient code into a high-level MLOps framework , so that optimisations benefit every training run and deployment rather than a single experiment. - Profile, benchmark and squeeze performance out of large-scale training and inference on thousands of GPUs. - Model LLM execution on various GPUs with high fidelity to assess hardware usage and build serving performance estimates. What We're Looking For - High technical competence for writing custom low-level kernels and pushing GPUs to their limits. - High expertise in the distributed computation infrastructure of current-generation GPU clusters. - Overall understanding of the field of generative AI ; knowledge of, or interest in, fine-tuning and using language models for applications. - Strong software-design instincts: testing, code review, CI/CD. - Self-starter, low-ego, collaborative. 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 .

About the Team We work across product, growth, and monetization to help people get more value from OpenAI’s products. We identify opportunities for machine learning, build and test early solutions, and partner with engineering and product to bring successful approaches into production. About the Role We’re looking for a data scientist who can enter an unfamiliar product area, find a useful ML application, and turn it into a working product intervention. You will own the work from problem definition and data preparation through modeling, experimentation, and launch evaluation. Projects will include personalization, next-best-action recommendations, lifecycle management, promotion targeting, and models of retention and customer lifetime value. You will help identify opportunities, build proofs of concept, evaluate, and iterate. In this role, you will: - Identify opportunities with product and business partners, define the decision a model will inform, and prioritize work by user value, feasibility, and expected impact. - Build datasets, features, reproducible training workflows, and models. You’ll use a combination of tools appropriate to the task at hand. - Translate predictions into product actions. Design experiments and use causal reasoning to establish whether those actions improve user and business outcomes. - Partner with engineers on integration, serving or batch scoring, monitoring, and rollout. Stay involved through launch and iteration. - Explain results and limitations clearly, document decisions, and build reusable methods that other teams can adopt. You might thrive in this role if you: - Have built and evaluated applied ML systems that influenced a product or business decision, with clear ownership of the modeling work. - Write effective Python and SQL and can investigate imperfect data, debug models, and make pragmatic implementation choices. - Build and schedule production scoring pipelines using dbt, airflow, and flyte. - Understand supervised learning, evaluation, experimentation, and the difference between predicting an outcome and changing it. - Can scope ambiguous problems, work across disciplines, and explain technical tradeoffs to colleagues with different backgrounds. - Are motivated by helping people use AI effectively and by learning unfamiliar product domains. - Are excited to take on challenging, impactful ML problems across multiple areas. - Have experience with recommendation systems, personalization, growth, retention, lifetime value, or treatment-effect modeling would be useful. We welcome candidates whose relevant experience comes from other domains. 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.

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 Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. Key Responsibilities - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. Requirements - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. Nice to Have - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers , or TRL. - Experience with trace mining to drive continuous improvement loops Location New York, New York Compensation $150,000-$300,000 base + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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.

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 believes AI capabilities are improving rapidly, and that AI safety policy needs to keep pace. Our Policy Development team translates technical insights into workable new policy ideas for governing frontier AI. As a member of the Policy Development team, you will drive our work on technical and cross-lab safety practices, deepen our work on frontier AI legislation, and develop new technical governance ideas that you pressure-test with researchers and carry into policy proposals. You will work closely with policy colleagues and with research, alignment, safety, and legal teams, and you’ll move easily between technical detail and how policy actually gets made. Key responsibilities - Help develop technical safety best practices and standards for frontier development, working closely with policy, research, and safeguards teams - Support cross-lab discussions and initiatives and serve as the Anthropic representative in key standards initiatives and groups - Review and give substantive input on federal, state, and global frontier AI safety bills, including on risk reporting, independent evaluation, and incident reporting, helping shape AI safety legislation development - Work with our external affairs policy teams to strengthen our frontier AI legislative framework - Contribute research and analysis across the policy team’s pacing workstreams, including developing novel policy proposals that address challenges related to the acceleration of AI R&D - Engage with the external AI safety and governance community to track new thinking and feed it into our own - Write clear memos and briefings that help leadership align on decisions Minimum qualifications - Are fluent in frontier AI safety and technical AI governance: the main players, proposals, and debates - Can read legislative text and comment usefully on it - Have expertise in any of the following domains: loss-of-control, alignment, compute governance, independent evaluation, model weight security, risk reporting - Write clearly for researchers, leadership, and policymakers - Can pick up new technical topics quickly and translate them to the broader policy landscape - Are comfortable with ambiguity and can own a project end to end Preferred qualifications - Are excited about standards work, and also want to contribute across the wider technical governance agenda - Have direct experience in an AI governance or safety research organization or frontier lab - Have experience working closely with standards bodies or industry consortia - Have experience developing and shaping technical legislation - Have published novel policy thinking on AI governance 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: $265,000 - $295,000 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.

About Pinecone Pinecone is the trusted AI knowledge company. Its trusted AI knowledge platform—including its Database, Nexus, and Marketplace products—power accurate, fast, and cost-effective AI applications for more than 10,000 customers and 1M developers worldwide. Pinecone's mission is to make AI knowledgeable. About the Team and Role We're looking for an Applied AI Engineer who loves building real applications with AI. You'll work across the stack, from backend services and retrieval pipelines to APIs and user-facing applications, turning new AI capabilities into working solutions. This is a hands-on engineering role for someone who enjoys moving quickly, experimenting with emerging technologies, and owning projects from initial idea to production. You'll work closely with our engineering and product teams, as well as customers and partners, to explore new use cases, build reference applications, and demonstrate what's possible with Pinecone's technology. The ideal candidate combines strong full-stack engineering skills with practical experience building LLM-powered applications and agentic systems. You should be equally comfortable discussing architecture, writing production code, and putting together a working prototype. Responsibilities - Design, build, and ship end-to-end AI applications using Pinecone’s retrieval and knowledge infrastructure. - Develop full-stack solutions spanning frontend interfaces, backend services, APIs, data pipelines, and LLM integration. - Build reference applications, integrations, and reusable components that help developers and customers adopt Pinecone. - Experiment with emerging AI patterns, including RAG, agents, tool use, context engineering, and agent memory. - Work with customers, partners, and internal teams to understand real-world problems and translate them into working software. - Evaluate and improve the quality, reliability, latency, and cost of AI-powered applications. - Share technical insights and best practices through code, examples, and technical content. - Bring learnings from building applications back into Pinecone’s product and engineering teams. What You’ll Bring to the Table You don't need to check every box, but you should enjoy building software and be excited about what AI makes possible. Full-Stack Engineering - Strong software engineering background with experience designing, building, and shipping production applications. - Proficiency in Python and/or TypeScript, including modern backend frameworks and frontend technologies such as React or Next.js. - Experience building APIs, integrating external services, and working with databases and cloud infrastructure. - Ability to independently take a project from rough requirements through implementation and deployment. Applied AI - Hands-on experience building applications using LLMs, embeddings, vector databases, or retrieval-augmented generation. - Familiarity with modern AI development tools, frameworks, and APIs. - Understanding of the practical challenges of building AI applications, including retrieval quality, evaluation, latency, reliability, and cost. - Curiosity about emerging patterns in agentic applications, context management, and AI-driven workflows. Ownership & Collaboration - A builder's mindset: you enjoy writing code, experimenting, and getting working software into users’ hands. - Comfortable working with ambiguous requirements and making pragmatic technical decisions. - Ability to communicate technical ideas clearly to engineers, customers, and other stakeholders. - Comfortable moving between rapid prototypes and production-quality implementations. - Interest in understanding how developers and customers use the technology and translating that feedback into better solutions. Bonus Points - Experience with Pinecone or other vector databases and search technologies. - Experience building agentic applications, agent memory systems, or complex RAG pipelines. - Contributions to open-source projects, developer tools, or technical communities. - Experience working directly with customers on technical projects. - Experience deploying and operating AI applications in production. Perks & Benefits - Comprehensive health coverage including medical, dental, vision, and mental health resources - 401(k) Plan - Equity award - Flexible time off - Paid parental leave - Annual Company Retreat - WFH Equipment Stipend Benefits and eligibility may vary by country of employment.

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building an AI powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for Software Engineers across the stack who are passionate about blending production-ready platform architecture with new tech and new paradigms. You’ll push the boundaries of OpenAI’s newest technologies to enable interactions and automations that are not only functional, but delightful. We value proactive, customer-centric engineers who can get the foundational details right (data models, architecture, security) in service of enabling great products. IIn this role, you will: - Own the development of new products, platform capabilities, and integrations from initial concept through launch and ongoing improvement. - Apply OpenAI’s latest models to knowledge systems, automation workflows, and AI agents. - Build reliable, maintainable software that can scale as our products, customers, and operational needs evolve. - Partner closely with engineers, data scientists, information systems architects, operations teams, and internal customers to understand problems and deliver effective solutions. - Work with product and research teams to share feedback, evaluate real-world performance, and improve how we apply new models. - Identify common patterns across use cases and turn them into reusable capabilities that support multiple teams and domains. You might thrive in this role if you have: - 4+ years of professional software engineering experience, excluding internships, at technology or product-driven companies. - Strong programming and software design fundamentals, with depth in areas such as backend, full-stack, product, or platform engineering. - Experience taking software from idea to production and making thoughtful tradeoffs across quality, speed, reliability, and security. - A customer-focused approach and the ability to turn loosely defined problems into practical solutions. - Comfort collaborating across disciplines, navigating ambiguity, and iterating quickly while building toward a long-term vision. - Curiosity about AI/ML and excitement about applying new models to real-world problems; direct AI/ML 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.

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 Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is a large distributed system: training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts. As an engineer in RL Engineering, you'll work on keeping that system secure as it scales. This is a hands-on engineering role. You'll work in the RL codebase and the infrastructure underneath it, alongside the engineers and researchers who build and use it. The system is large and changes as fast as the research does, so security work here has to keep up with that pace without costing performance or velocity. We're hiring from two backgrounds: security engineers who want to work on large-scale ML systems, and ML systems or research engineers who want to work on security. Strong candidates have depth in one and real interest in the other. Key responsibilities - Design, build, and operate security controls for RL training systems and the infrastructure they run on - Work across the stack (orchestration, environments, training, inference) wherever the work is needed - Review designs and code across the RL stack, find security problems, and fix them - Build shared libraries and tooling that other RL engineers and researchers build on - Build the observability needed to understand what these systems are doing - Work with researchers and performance engineers to make sure security changes preserve training correctness and performance - Write clear design documents for what you build Minimum qualifications - Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go - Experience designing, building, and operating large-scale distributed systems or security systems in production - Strong understanding of security fundamentals - Working knowledge of Linux, containers, and cloud infrastructure - Experience debugging complex problems across many hosts and services - Ability to reason about tradeoffs between security, performance, and reliability - Strong written communication, including design documents Preferred qualifications - Experience running ML training or inference infrastructure at scale - Experience with infrastructure security, such as isolation, access control, networking, or identity - Experience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scale - Experience building observability for large fleets - Experience supporting research teams or other fast-moving internal users - Familiarity with reinforcement learning or large language model training workloads The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 - $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

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 customer-facing teams are often the first place a customer sees what Claude can do. As a Demo Engineer, you'll build the demos, reference implementations, and reusable tooling that help those teams make new capabilities tangible, relevant, and trustworthy, ideally within days of a product launch rather than weeks after. This role sits between product engineering, technical storytelling, and GTM execution. You'll own ambiguous, high-leverage problems end to end: prototyping an agentic experience for a new capability, then hardening it into something reliable that other teams can run on their own. You'll work closely with Product, Engineering, Marketing, Operations, and our sales and solutions teams, and you'll bring what you learn from customer-facing work back to the people building the products. Because a demo is frequently someone's first impression of what our models can and can't do, accuracy and honesty matter as much as polish. Success in this role looks like customer-facing teams demonstrating new capabilities sooner and with more confidence, recurring requests becoming reusable assets rather than one-off projects, and field insights shaping product and launch-readiness decisions. Responsibilities - Own demo readiness for new and priority Claude capabilities, including environments, integrations, synthetic data, evaluations, reliability checks, and fallback paths - Build prototypes, agents, and reference flows that make complex capabilities concrete and tie them to clear customer outcomes - Turn recurring requests into reusable accelerators such as companion apps, templates, Skills, plugins, and self-service demo packages that scale across customer-facing teams - Partner with GTM colleagues on high-impact customer moments, unblock critical technical gaps, and spot the patterns worth turning into shared assets - Build internal agentic systems that automate demo preparation, validation, and asset maintenance, so demos stay current as products change - Translate patterns from customer-facing work into product feedback, launch-readiness priorities, and systemic improvements with Product and Engineering - Define and raise the bar for demo quality across accuracy, safety, reliability, usability, and adoption - Decide when a customer need calls for a bespoke build and when it should become a shared capability You may be a good fit if you have - Proficiency in Python or TypeScript, with experience shipping working software end to end - Hands-on experience building applications or agents on top of LLM APIs, including prompting, tool use, and retrieval - Experience designing integrations with third-party APIs, data sources, and services - The ability to take an ambiguous capability or customer need to a working prototype quickly, and then make it reliable - Clear communication of technical concepts to both technical and non-technical audiences, including sales and solutions teams - Comfort collaborating across Product, Engineering, Marketing, Operations, and GTM teams - Experience in a demo engineering, solutions engineering, sales engineering, forward deployed engineering, developer relations, or product engineering role - A track record of building reusable internal tools, templates, or self-service assets that other teams adopted - Hands-on experience with Claude Code, the Claude Agent SDK, the Model Context Protocol (MCP), Skills, or plugins - Experience building evaluation or validation harnesses for AI systems, including reliability checks and graceful fallbacks - Experience building always-on or scheduled agentic systems that automate internal workflows - Experience building synthetic or sanitized datasets that make demos realistic without exposing sensitive information - Front-end or product design skills that help demos feel polished and intuitive - Experience supporting product launches or running launch-readiness programs - A history of turning field feedback into concrete product input that influenced a roadmap - A passion for making powerful technology safe and beneficial, and a commitment to representing model capabilities accurately and honestly The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 - $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About the role We’re looking for a product data scientist to help OpenAI create more value and drive sustainable growth for young people, families, and learners. You’ll drive product data science across under-18 audiences, emerging opportunities for children under 13, family experiences, and learning and education more broadly. You’ll help decide where we should invest, what we should build, and how we’ll know it is working. This means understanding distinct audience needs, identifying promising use cases, and turning evidence into a clear product strategy. Your work will connect discovery and early product development with adoption, retention, and sustained user value. You’ll partner across Chat Product, Growth, Foundations, SafeSys, and other teams, working closely with product managers, engineers, designers, and researchers. The role focuses and owns product value and growth while dedicated teams own policy and safety. In this role, you will: - Shape strategy and prioritize opportunities. Size unmet needs and growth opportunities across audiences, use cases, and product experiences. Help teams choose where to invest and sequence work based on expected user value, reach, evidence, and effort. - Define what value and success mean. Develop an audience-specific measurement framework spanning activation, task success, learning progress, satisfaction, and durable retention. Connect these measures to product goals and assess whether repeat use reflects meaningful benefit. - Understand users and growth drivers. Analyze journeys, funnels, and cohorts to uncover where people find value, where they struggle, and what helps them return. Combine behavioral data with surveys and user research to explain differences across ages, family roles, and learning contexts. - Measure what changes actually cause. Design experiments and holdouts to evaluate product and model changes. Apply causal methods when randomization is impractical, make assumptions explicit, and account for seasonality, audience composition, and effects that differ across segments. - Turn findings into product decisions. Work with partners from initial hypotheses through launch and iteration. Recommend what to build, change, expand, or stop, explaining expected impact, uncertainty, and tradeoffs. Follow through to determine whether decisions delivered the intended results. - Build reliable measurement. Partner with engineering on instrumentation, dataset quality, and consistent audience definitions. Create reusable analyses and dashboards that make progress visible and let teams answer recurring questions independently. - Create alignment across teams. Bring a coherent view of audience value to work spanning multiple roadmaps. Help partners agree on priorities, success criteria, and the next questions to resolve, even when ownership is distributed and evidence is incomplete. You might thrive in this role if you have: - A record of influencing product strategy and improving user outcomes through hands-on data science, including work from an ambiguous question to a decision and measurable impact. - Strong SQL and Python skills, sound statistical judgment, and practical experience with experiments, causal inference, cohort analysis, and measurement design. - The ability to develop useful definitions of product value, validate imperfect proxies, and distinguish short-term metric movement from lasting improvement. - Clear communication and strong product judgment. You can make a recommendation, explain its limits, and influence collaborators across functions without relying on formal authority. - Comfort setting priorities independently across a broad scope, staying close to users, and moving between strategic questions and detailed analytical work. Helpful experience Experience with consumer product growth, youth or family products, learning and education, or generative AI would be valuable. We also welcome experience measuring learning outcomes, combining quantitative and qualitative research, or evaluating products whose value emerges over time. 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.

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 hands-on People Operations Specialist to join our People team and keep our day-to-day people operations running smoothly. You'll work side by side with the broader HR team — HRBP, People Ops, Recruiting, and Immigration — to make sure the many moving pieces of a fast-growing company land cleanly: new hires onboard without a hitch, our systems and data stay accurate, and employees get quick, clear answers when they have questions. This role is ideal for someone early in their HR career who wants breadth. You'll touch HRIS, onboarding, contractor operations, immigration support, internal documentation, and employee recognition — and you'll get real ownership in each area. We're looking for someone who's highly organized, comfortable shifting priorities, and able to unblock themselves and keep things moving without waiting to be told how. What You'll Do HRIS & Data Integrity - Own day-to-day updates in our HRIS — start date changes, title and job detail adjustments, reporting line changes, and other employee record maintenance. - Run regular internal data audits to catch and correct discrepancies before they become downstream problems for payroll, benefits, or reporting. - Partner with People Ops, Finance, and IT to keep employee data consistent across systems. Onboarding Logistics - Coordinate end-to-end onboarding logistics for new hires so their first day is seamless, including: - Monitoring background check status and following up on anything pending or flagged. - Completing I-9 verifications and driving follow-ups to ensure timely, compliant completion. - Coordinating with IT on laptop provisioning, email and account setup, and name or address changes. - Managing seat assignments and workspace readiness in partnership with Workplace. - Ordering and preparing new hire swag and welcome materials. - Help facilitate our weekly new hire onboarding sessions — prepping materials, managing logistics and the calendar, presenting portions of the agenda, and gathering feedback to improve the experience over time. - Serve as a friendly first point of contact for new hires, answering pre-start and first-week questions. Contractor Lifecycle Management - Own the contractor lifecycle end to end: onboarding (agreements, signatures, background check bypass proof), contract timeline tracking (start and end dates, early expiration flags, extensions and conversions with managers and Finance), and offboarding (access and equipment return with IT, final documentation). - Keep contractor records, status, and dates accurate at every stage. Immigration Support - Support immigration case processing in partnership with our People team and outside counsel — gathering documents, tracking case status, and keeping timelines on track. - Handle basic immigration questions from employees, candidates, and the recruiting team, escalating complex matters appropriately. - Maintain accurate immigration records and calendar key deadlines and expirations. Internal Documentation - Own our internal HR wiki — keeping pages current, accurate, and easy to navigate as policies and processes evolve. - Document new and changed processes so the team has a reliable single source of truth. Employee Recognition - Support administration of our recognition program, including managing award winner prizes, swag, and fulfillment logistics. - Help keep the program visible and running on a consistent cadence. What We're Looking For - Degree in Human Resources or a related field, plus 2-3 years of experience in an HR Generalist or HR Specialist role. - Highly organized, with a track record of juggling a wide span of workstreams and keeping details from slipping through the cracks. - Resourceful and self-directed — comfortable figuring out a solution when there's no playbook, and able to unblock yourself to get things done. - Comfortable pivoting as priorities shift, and able to re-prioritize quickly without losing track of what's still open. - Strong written and verbal communication skills, with sound judgment about what to handle directly and when to escalate. - Discretion and good judgment in handling confidential employee information. Nice to Have - Experience supporting immigration cases (H-1B, TN, O-1, green card processing, or similar). - Experience in a startup or other high-growth, fast-paced environment. - Hands-on experience with an HRIS such as Rippling - Enthusiastic, positive, and brings great energy — someone people are genuinely glad to work with. 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.

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 Life Sciences team is building a research group focused on biological discoveries by combining AI with hands-on biological research. We're seeking a research scientist who combines deep chemistry knowledge with machine learning expertise to join the team. Our goal is to speed up progress in the life sciences by an order of magnitude, and this role puts that mission into practice. You'll be a computational chemist who knows reactions, synthesis, and medicinal chemistry in depth and has hands-on experience training and evaluating machine learning models. Above all, you'll build the reinforcement learning environments, datasets, and evaluations that teach Claude chemistry. Working alongside our bench chemists and AI researchers, you'll turn real chemistry problems and experimental data into training tasks and measure whether the models get better at them. This role is fully on-site in the San Francisco Bay Area. Key responsibilities - Design and build reinforcement learning environments for chemistry end to end, including task design, data curation, automated grading, and checks against shortcuts and data leakage - Design and source new experimental datasets, environments, and evaluations with our bench chemists, and external research and academic partners - Develop evaluations that measure model performance on real chemistry tasks, such as reaction outcome prediction, synthesis planning, structure elucidation, and compound design, and feed results back to research teams - Run and analyze training experiments with AI research teams, diagnose where models fail at chemistry, and prioritize what to build next - Ensure datasets and environments are high quality and well documented, including sources, train and test splits, and failure modes - Communicate findings clearly to chemistry, AI research, and life sciences audiences Minimum qualifications - PhD in chemistry, computational chemistry, or a related field - Deep knowledge of organic and medicinal chemistry, including reactions, synthesis, and SAR, with experimental data as your ground truth - Strong Python skills and solid machine learning fundamentals, with hands-on experience training and evaluating models - Comfort navigating ambiguity and defining problems in a rapidly evolving research environment - Ability to work independently while collaborating effectively across cross-functional teams, with strong written and verbal communication skills Preferred qualifications - Experience with reinforcement learning, large language models, or building evaluations and benchmarks - Track record of supporting drug discovery programs alongside medicinal and synthetic chemists - Experience curating chemistry datasets from the literature, patents, or lab notebooks, including reaction, ADMET, and spectroscopic data - Cheminformatics and molecular modeling skills, for example RDKit, docking, free energy calculations, or quantum chemistry - Hands-on synthetic or medicinal chemistry experience at the bench - Publications, patents, or open-source software demonstrating scientific impact The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 - $320,000 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.

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 This is a chance to build the frontier LLM evals that shape the next generations of flagship models. Could a model design a computer chip, or find the backdoor an attacker left in a network? Public benchmarks can't tell us, as they're generally not a good measure of real work. As an Evaluation Engineer, you'll own evals from start to finish. You'll run workshops with customers, industry experts and our customer-facing teams to understand their most important industry use cases (e.g., an engineer updating a part in CAD software), and help decide which are worth building first. You'll also look beyond today's use cases and design moonshot evals for work no model can do yet, so Mistral gets there first. Then you'll turn each one into a benchmark, often one where an agent has to do the work inside real software. You'll source the data, decide how to score it, and run it on every new Mistral model and on competitor models. When our models fall short, you'll work with the post-training teams to close the gap. When they catch up, you'll make the eval harder. You'll write up and present your results so senior leaders can act on them. They also give our go-to-market teams evidence of where Mistral leads. You'll learn new fields quickly. One month you might be learning how chip designers check their work, and the next how a bank investigates a flagged payment. The team is new and fast-paced, and you'll have a lot of autonomy. You'll spend a lot of time speaking with people across Mistral to work out what matters most, then decide what to build. What You Will Do - Run discovery with customers, industry experts and teams across Mistral, then help decide which use cases are worth building first. - Design new benchmarks for industry use cases and frontier capabilities, including how they're scored. - Build evals where agents work inside real software (e.g., CAD and simulation tools), and run them on our models with checks that the results stay reliable over time. - Stress-test existing evals to find flaws and bugs before we rely on them. - Source data with expert vendors. Where customer data can't leave the customer, build realistic proxy or synthetic data instead. - Write up and present what you find so leaders across Mistral can act on it. - Help other teams build their own evals, with tools and guides they can reuse. What We're Looking For Experience - 2+ years of industry experience (e.g., in software, AI, or consulting), or a PhD. - A software engineering or research background, with experience writing code that others can build on. - Experience working directly with customers, industry experts, or other teams (e.g., through consulting, solutions engineering, or research collaborations). - Experience building something with LLMs. - Comfort working with large datasets, including building and cleaning them. Technical - Strong Python skills. - Comfortable working in a large, shared codebase and getting your code through reviews by other teams. - A strong understanding of LLM training, inference, and evaluation. Communication - You enjoy speaking with people and are good at it. - You write clearly. A short doc or deck from you is enough for a busy leader to make a decision. - Confident presenting to both technical and non-technical audiences. - Fluent in English. How you work - High energy, and you don't need a roadmap. You move independently and handle uncertainty with confidence. - Proactive and high-agency. You spot what needs doing and get it done. - You make good decisions about what to build first and can explain why. - Low-ego, collaborative, and eager to learn. - Curious, with a track record of learning things outside your work or studies. You can get to grips with a new field in a few weeks. NICE TO HAVE - Experience building AI evaluations, especially for industry applications. - Published research on evals or contributions to open-source evaluation frameworks. - Experience building datasets, generating synthetic data, developing labelling guidelines, or working with annotation vendors. - A background in an industry outside software (e.g., engineering, finance, or science). 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 .

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 at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. Key Responsibilities - Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development - Independently lead small research projects while collaborating with team members on larger initiatives - Design, run, and analyze scientific experiments to advance our understanding of large language models - Optimize and scale our training infrastructure to improve efficiency and reliability - Develop and improve dev tooling to enhance team productivity - Contribute to the entire stack, from low-level optimizations to high-level model design Qualifications - Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field - Strong software engineering skills with a proven track record of building complex systems - Expertise in Python and experience with deep learning frameworks (PyTorch preferred) - Familiarity with large-scale machine learning, particularly in the context of language models - Ability to balance research goals with practical engineering constraints - Strong problem-solving skills and a results-oriented mindset - Excellent communication skills and ability to work in a collaborative environment - Care about the societal impacts of your work Preferred Experience - Work on high-performance, large-scale ML systems - Familiarity with GPUs, Kubernetes, and OS internals - Experience with language modeling using transformer architectures - Knowledge of reinforcement learning techniques - Background in large-scale ETL processes You'll thrive in this role if you - Have significant software engineering experience - Are results-oriented with a bias towards flexibility and impact - Willingly take on tasks outside your job description to support the team - Enjoy pair programming and collaborative work - Are eager to learn more about machine learning research - Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects - Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research - View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximize the impact of your insights - Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long-term. Sample Projects - Optimizing the throughput of novel attention mechanisms - Comparing compute efficiency of different Transformer variants - Preparing large-scale datasets for efficient model consumption - Scaling distributed training jobs to thousands of GPUs - Designing fault tolerance strategies for our training infrastructure - Creating interactive visualizations of model internals, such as attention patterns 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. 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.

About the Team Our team builds classification and evaluation systems that give post-training and research teams fast, reliable feedback on model behavior. We combine machine learning and production engineering to make these capabilities accurate, efficient, and useful at scale, helping researchers assess changes and improve models and products. We work closely with research teams to develop useful measurements and make them practical to run. Our work spans classifier development, rigorous evaluation, and efficient production inference, with ownership from initial experimentation through deployment and continued improvement. About the Role We’re looking for a machine learning engineer to develop new classification and evaluation capabilities and bring them into production. You’ll help turn open-ended questions about model behavior into well-defined ML problems, build methods that address them, and establish how reliably those methods work. This role combines traditional machine learning, model evaluation, and real-time engineering. You’ll own classifiers throughout their lifecycle, including supervised fine-tuning, distillation, evaluation, deployment, and production inference. You’ll work closely with researchers to identify valuable problems and with software engineers to make promising approaches useful at scale. In this role, you will: - Build, deploy, and operate production classification and evaluation systems that provide useful feedback to post-training and research teams. - Optimize production inference, including model serving, batching, caching, throughput, latency, compute utilization, and cost. - Train and optimize classifiers using supervised fine-tuning and distillation, validating quality and efficiency before deployment. - Own the reliability and observability of deployed classifiers, diagnose production issues, and improve their performance over time. - Design rigorous evaluations that assess accuracy, calibration, generalization, and potential measurement bias while guiding production tradeoffs. - Partner with software engineers to integrate models into reliable execution systems and support safe rollouts. - Build reusable engineering tools that make classifier training, evaluation, deployment, and iteration faster and more repeatable. - Work with post-training researchers and data scientists to translate their needs into modeling objectives, evaluation criteria, and production requirements. Your background might look something like - Experience taking ML projects from problem formulation and experimentation through production deployment. - Strong foundations in supervised learning, statistics, and experimental design. - Practical experience evaluating models, investigating systematic errors, and working with imperfect labels. - Strong software engineering skills and the ability to build maintainable production ML systems. - Experience reasoning about inference performance and the tradeoffs between quality, latency, and compute cost. - The ability to combine careful scientific judgment with a practical approach to shipping and operating software. - Comfort working closely with researchers and engineers on open-ended problems. - Fluency in using AI agents to move quickly across multiple workstreams in a fast-paced environment. - Experience with model distillation, representation learning, calibration, or efficient inference is a plus. 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.

About the Team The OpenAI for Government AI Architect team partners with public sector organizations to turn OpenAI's most capable models into meaningful, real-world impact. We work with government agencies, public institutions, and partner organizations serving the government to identify where AI can advance critical missions, design secure and scalable solutions, and help those solutions move from early exploration into sustained production adoption. The team brings together technical strategy, customer partnership, and practical deployment expertise, working closely with Sales, Product, Engineering, Research, Security, Global Affairs, and specialist delivery teams to help public sector customers adopt advanced AI responsibly and effectively. About the Role As an AI Architect, you will be the senior technical owner for a named portfolio of customers and the primary technical counterpart to their leadership teams. You will shape each customer's AI strategy and guide their journey from pre-sales discovery and solution evaluation through deployment, adoption, and measurable mission impact. You will own the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex, and other agentic AI solutions. In partnership with the Account Director, you will translate mission priorities into a focused use-case portfolio, an actionable adoption roadmap, and a clear path to durable customer value. The Account Director leads the overall account strategy and relationship, while you lead the technical strategy, customer journey, and path to production impact. You will remain accountable for the technical outcome while bringing in the right specialists across deployment, implementation, enablement, security, product, and partners to provide deeper expertise and execute work where needed. This role calls for strong public sector fluency, sound architectural judgment, and the ability to move confidently between executive strategy and hands-on technical conversations. This role is based in Munich or London. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: - Serve as the primary technical advisor and long-term technical relationship owner for a named portfolio of public sector customers and pre-sales prospects. - Partner with Account Directors on account strategy while owning the technical account plan, technical milestones, adoption priorities, and expansion opportunities. - Lead discovery with agency leaders, mission owners, executives, and technical teams to identify, qualify, and prioritize use cases tied to meaningful mission and operational outcomes. - Develop clear Applied AI Architectures spanning models, applications, data, integration, identity, security, privacy, governance, evaluation, and deployment. - Guide customers through technical evaluations, demonstrations, workshops, prototypes, and proofs of value, building confidence in both the solution and its path to production. - Help customers navigate the security, compliance, governance, and deployment requirements that shape AI adoption in the public sector. - Maintain a focused use-case portfolio with clear decision criteria, ownership, blockers, success measures, delivery needs, and adoption plans. - Develop trusted relationships and technical champions across CIOs, CTOs, CISOs, Chief Data and AI Officers, program leaders, engineering teams, and other customer stakeholders. - Qualify and coordinate support from Deployment Engineering, implementation, training and enablement, security, product and domain specialists, partners, and other delivery teams. - Remain accountable for technical progress and customer outcomes while ensuring delivery teams own implementation execution once engaged. - Track adoption, usage, account health, production readiness, and measurable mission impact, intervening early when risks threaten value realization. - Apply public sector and mission expertise to recognize repeatable patterns, sharpen customer priorities, and identify relevant expansion opportunities. - Share customer insights with Product, Engineering, and Research, translating field learnings into better products, architecture guidance, and reusable practices. You might thrive in this role if you: - Have significant experience in customer-facing technical roles such as solutions architecture, solutions engineering, technical account leadership, AI deployment, or technical customer success. - Have guided complex organizations from technical evaluation through production adoption and measurable impact. - Have experience working with government agencies, public institutions, or government contractors and understand how mission priorities, security, compliance, governance, and procurement considerations shape technology adoption. - Build credibility with senior technical and government leaders while communicating equally well with hands-on engineers and program teams. - Bring strong software and cloud architecture foundations, including APIs, distributed systems, data integration, identity, security, and privacy. - Understand modern AI systems, frontier models, agentic applications, model evaluation, retrieval, and enterprise AI workflows. - Can prototype, explain technical tradeoffs, and work confidently with APIs, SDKs, and languages such as Python or JavaScript. - Exercise sound judgment about when to go deep personally, when to involve specialists, and how to establish clear handoffs and ownership. - Have experience developing technical account plans, prioritizing complex customer portfolios, and connecting adoption to measurable outcomes. - Bring meaningful expertise in a relevant public sector mission or customer segment. - Communicate clearly and can turn ambiguity into a practical technical narrative, executive decision, or action plan. - Work collaboratively across disciplines and care deeply about helping public sector organizations deploy advanced AI safely and responsibly. 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.

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 RL teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Fable 5.1 and Claude Opus 5.5. Our work spans several key areas: - Developing systems that enable models to use computers effectively - Advancing code generation through reinforcement learning - Pioneering fundamental RL research for large language models - Building scalable RL infrastructure and training methodologies - Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implementing our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the role We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to design silicon. Hardware design is difficult and unforgiving – exactly the sort of domain we want Claude to excel at. You'll leverage your chip design expertise and turn it into tasks and signals for models to learn from. Specifically, you will: - Invent, design, and implement RL environments and evaluations for agentic RTL generation, design (including formal) verification, physical design optimization. - Work on cross-cutting RL considerations such as EDA-tool latency optimization and proxy rewards. - Conduct experiments and shape our roadmap. - Deliver your work into research and production training runs. - Collaborate with other researchers and engineers across and outside Anthropic. You may be a good fit if you: - Have expertise in ASIC or FPGA design: RTL, design verification (UVM, formal methods, coverage-driven), physical design (synthesis, place-and-route, timing closure), PPA optimization, DFT, ECOs. - Are fluent with industry EDA tools and processes. - Have taped out chips and have experience going from spec to silicon. - Know how to 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: - Experience with reinforcement learning, evaluations or environments. - Built tooling or automation around chip design flows. - Worked on ML accelerators or high-performance compute hardware. - Familiarity with high-level synthesis or architecture simulators. 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. 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.

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 Anthropic Residency is our paid, fixed-term research program, with placements lasting between six weeks and six months. We are looking for people who have led ambitious work in a variety of technical fields and want to transition to full-time work focused on making sure AI systems are safe and beneficial for all of humanity. If you are a professor in a quantitative discipline, a technical founder or a staff-level engineer and want to transition to work on transformative AI, we want to hear from you. Background in machine learning is not required. What to expect - A concrete, scoped project matched to your background, with direct mentorship from Anthropic researchers - Access to Claude models and GPU compute - Connection to the broader AI safety and security research community Interview process The interview process will include an initial application, recruiter screen, technical assessment, research discussion and a reference check. Applications for this round close on November 22, 2026 (11:59 PM PT). We expect to make offers in January 2027. You may be a good fit if you - Are motivated by making sure AI is safe and beneficial for society as a whole - Are excited to transition into working on empirical AI research full-time - Have led ambitious work in a variety of technical fields (professor in a quantitative discipline, a technical founder or a staff-level engineer) - Thrive in fast-paced, collaborative environments - Can implement ideas quickly and communicate clearly Strong candidates may also - Have experience authoring research papers in machine learning, NLP, or AI safety - Have experience with LLMs, reinforcement learning or Kubernetes clusters and complex shared codebases Mentors and research areas Potential Anthropic mentors include: - Sara Price : leads the Alignment Training team; background in data science - Ethan Perez : leads the Alignment Science team; background in machine learning - Evan Hubinger : leads the Alignment Stress-Testing team; formerly at The Machine Intelligence Research Institute (MIRI) - Samuel Marks : leads the Scalable Oversight team; background in mathematics - Elana Simon : researches the interpretability of language models and biological models; background in biomedical informatics - Belinda Li : researches how language models represent the world, users, and themselves; background in natural language processing (PhD, MIT) - Jack Lindsey : leads the Model Psychology team; background in theoretical neuroscience - Nicholas Carlini : researches adversarial machine learning and AI security; previously at DeepMind and Google Brain - Jascha Sohl-Dickstein : works at the intersection of safety and pretraining; background in physics and neuroscience, formerly Principal Scientist at Google Brain Residents will work on empirical research questions in collaboration with Anthropic's research teams. Areas we are particularly interested in include: AI safety & alignment - Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains. - Adversarial Robustness and AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. - Model Organisms: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. - Model Internals and Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures. - Safeguards Research: Developing robust defenses against adversarial attacks, comprehensive evaluation frameworks for model safety, and automated systems to detect and mitigate potential risks before deployment. - AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations. AI security & frontier red-teaming - Stress-testing frontier models to understand the full extent of their current capabilities in fields such as cybersecurity, robotics or cryptography. ML systems & reinforcement learning - Improving how frontier models are trained and building the infrastructure behind that research, from model architecture, optimizers and training data to accelerator simulators, hardware backends and RL environment pipelines. For a fuller picture of the questions we care about, see our Recommendations for Technical AI Safety Research Directions and recent publications from our Alignment , Interpretability and Frontier Red teams. Logistics - Duration: Placements are six weeks, three months or six months, depending on team fit and candidate preferences. Other lengths between three and six months are possible by exception. - Location: This application is for a remote UK position, with the option to work from our London office. However, we prefer that Residents work from our San Francisco office, where most of our research staff is based, but remote participation is possible, especially for shorter placements. Most full-time research roles at Anthropic require relocation to San Francisco. Remote participants need to be based in a country where Anthropic can hire. - Commitment: Full-time role for the duration of the residency. - Compensation: £265,000 to £375,000/year pro-rated for the duration of the residency + benefits - Visa sponsorship: We sponsor visas for placements of three months or longer. For six-week placements we encourage remote participation from a country where Anthropic can hire. Applicants may also be considered for the Anthropic Fellows Program . 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: £265,000 - £375,000 GBP Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. The Role We're looking for motivated and tech-savvy Sales Development Representatives (SDRs) with a strong interest in AI to join our growing sales team. In this role, you’ll play a key part in building a healthy pipeline for our Account Executives by qualifying inbound leads and proactively prospecting into high-value target accounts. This is an opportunity to be at the frontlines of a fast-moving AI company, engaging in thoughtful, technical conversations with a knowledgeable customer base. The ideal candidate is results driven, exhibits strong intellectual curiosity of the evolving AI space, and can operate in a fast-paced, highly-dynamic start up environment. You should be comfortable initiating outreach, handling nuanced product discussions, and helping prospects understand the impact of generative AI on their business. Key Responsibilities - Strategically prospect into key accounts across email, calling and Linkedin, communicating Fireworks AI’s unique value proposition - Consistently meet new business opportunity and pipeline generation targets - Craft personalized, tailored outreach through various research methods to prioritize the right accounts and prospects - Qualify and engage inbound leads, ensuring a smooth transition to our Account Executive team - Act as a brand ambassador, educating prospects on the power and potential of our inference solutions - Collaborate with Sales and Marketing to refine messaging and outreach strategies based on market feedback - Stay current on AI/ML trends to conduct informed, relevant conversations with technical and business audiences Minimum Qualifications - Bachelor’s degree or equivalent practical experience - Demonstrated interest in technology sales, with a strong interest AI and machine learning - Excellent communication and interpersonal skills; able to engage confidently with technical stakeholders - Self-motivated and organized, with the ability to manage multiple priorities in a fast-paced environment Preferred Qualifications - Previous startup or entrepreneurial experience, with a proactive and adaptable mindset - Prior experience in a customer facing role, ideally in SaaS, AI, or emerging tech - Familiarity with CRM systems and sales engagement tools (e.g., Salesforce, Outreach, Apollo, etc.) - Degree in engineering, computer science, or a related technical field - Active interest in AI/tech communities with a demonstrated commitment to continuous learning in the space Fireworks AI's goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. The estimated range for total on target earnings (including base salary and on target incentive pay) for candidates in the San Francisco/New York City Area for this role is $85,000 - $100,000 per year. Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

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 Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact. Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. By joining the team you'll 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 - You’ll individually help deploy into production use cases with a considerable business impact across various industries. - You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. - You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning. - You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. - Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback 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 have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products - You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces. - You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases - You have deep understanding of concepts and algorithms underlying machine learning and LLMs - You have strong technical coding skills in Python - You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences Ideally you have: - Contributed to open-source projects in particular in the space of LLMs - Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager - You have experience with deep learning with Pytorch 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 .

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 hiring our first SDR Manager to help build Fireworks’ business development function from the ground up. You’ll lead, coach, and grow a team of SDRs who qualify inbound interest from developers and enterprises and prospect into high-value target accounts. Together, you’ll create the pipeline that drives our Account Executive team. This is a builder role. You’ll own the team’s performance and development while designing the playbooks, systems, and AI-powered workflows behind our top-of-funnel motion. We’re looking for a hands-on, first-line leader who gets results through great coaching. They should be fluent in AI tooling and process design, let data guide their decisions, and bring a “can do” attitude to every problem. They should be excited to define how sales development works at one of the fastest-growing companies in AI. KEY RESPONSIBILITIES - Hire, onboard, and lead a team of SDRs, scaling the team as Fireworks grows - Coach reps through regular 1:1s, call and email reviews, and hands-on skill development, building a clear path from BDR to AE - Own team performance across activity, conversion rates, meetings booked, pipeline generated, and quota attainment - Build repeatable playbooks for inbound qualification and outbound prospecting, including ICP, personas, messaging, and AE handoff criteria - Partner with Marketing to quickly convert inbound and product-led signals (signups, usage, events) into qualified opportunities - Design and deploy AI workflows and automations for account research, prioritization, personalization, and reporting, freeing reps to focus on high-value conversations - Continuously audit and improve SDR processes, from lead routing and follow-up speed to sequencing and handoffs, so the team operates efficiently at scale - Build dashboards and reporting that give the team and leadership clear, real-time visibility into funnel health - Use data to find bottlenecks, run experiments, and turn insights into action quickly - Work with Sales leadership and RevOps to align on target accounts, territories, lead routing, and pipeline goals MINIMUM QUALIFICATIONS - 2–4 years of direct, first-line management experience leading SDR/BDR teams - A proven track record of exceptional coaching and development, with reps promoted into AE or leadership roles and teams that consistently hit or exceed targets - Strong AI tooling and process skills, with hands-on experience building AI workflows that measurably improved sales productivity (e.g., Clay, AI agents, LLM-based prompts and automations) - A data-driven “can do” mindset: you dig into the numbers, spot what’s broken, and fix it yourself rather than waiting for a solution - Experience managing team performance through metrics, funnel analytics, and pipeline forecasting - Prior experience as an individual contributor in sales development or a closing role - Excellent communication and organizational skills, and comfort engaging technical buyers PREFERRED QUALIFICATIONS - Experience building a sales development function from scratch at a high-growth startup - Background in AI, developer tools, cloud infrastructure, or other technical SaaS - Experience with both high-volume inbound and targeted outbound motions - Fluency with a modern GTM stack (e.g., Salesforce, Outreach, Apollo, LinkedIn Sales Navigator, Gong) - Passion for developing early-career sales talent and an active interest in the AI/ML space Fireworks AI’s goal is to provide competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided. Why Fireworks? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI Engineer on the Startups team at Anthropic, you will be a trusted technical advisor to the top AI-native life sciences and biotech startups as they grow from early product to scale. Some of these companies build products on Claude that they sell to the rest of the industry, and others do the science themselves and want Claude woven into how their own research runs, and this role works with both. You'll lead deep technical engagements, partnering directly with startup engineering and scientific teams to help them build their products on Claude and run their own research with it, advising on implementation and agent design as they build what is newly possible with AI in the life sciences. You will bridge the gap between what Claude can do and what the life sciences need, working alongside some of the strongest teams in the field on problems that matter and pushing the boundaries of AI in science as you go. Working closely with Applied AI Architects, Account Executives, and Anthropic's Product, Engineering, and Research teams, you'll help startups build at the edge of what is possible with Claude. You'll leverage your AI engineering expertise and your scientific domain knowledge to develop custom evaluation frameworks, design scalable architectures, and create the technical resources that enable life sciences startups to succeed with Claude. Responsibilities - Serve as a deep technical advisor to high-potential life sciences and biotech startups, whether Claude sits inside the product they sell or inside the way they make discoveries, working alongside them to build innovative use cases that push the boundaries of AI in scientific research and development - Work hands-on with startup engineering teams and their scientists through pair programming and architecture reviews that accelerate their development, and understand their scientific workflows end to end so that your guidance fits into real research pipelines - Develop prototypes and technical documentation, including evaluation suites, scientifically grounded benchmarks, AI engineering techniques, and architecture diagrams, that enable startups to build, operate, and scale with Claude - Create reference implementations and sample code that many companies can adopt without starting from scratch, such as example MCP servers for domain-specific data sources like genomics platforms, literature databases, and experimental repositories, along with agent skills for common scientific workflows - Collaborate closely with Applied AI Architects to maintain context and continuity across customer engagements - Identify patterns across engagements, including what is hard about deploying AI in the life sciences such as heterogeneous data, auditability requirements, and the gap between a working prototype and a system that scientists trust, and contribute insights back to Product, Engineering, Research, and the broader Applied AI team, including feedback on the model capabilities and product features that would most accelerate discovery work - Create technical content for startup audiences including documentation, tutorials, and sample code - Represent Anthropic across the life sciences startup ecosystem and foster community engagement through hackathons, webinars, technical office hours, in-person founder events, and research show and tells - Travel to customer sites for workshops, implementation guidance, and relationship building You may be a good fit if you have - Deep experience in the life sciences or biotech, gained through research or industry work in areas such as genomics, drug discovery, molecular design, lab automation, or clinical development, along with strong opinions of your own about how to bridge the gap between what AI can do today and what the life sciences need - 4+ years of technical experience as a software engineer, ML or research engineer, computational biologist, research scientist, or technical founder, with either production experience building LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale, or a track record of successfully applying AI to real scientific work in the lab or in research - Experience with startups or high-growth companies and a love of working with founders and small teams that move quickly - Strong technical communication skills, with the ability to translate complex AI concepts into architectural decisions and actionable implementation plans for both engineering and scientific audiences and to run technical workshops, hackathons, or developer-focused events - A collaborative approach to working across teams, the ability to context-switch across scientific domains and use cases, and a passion for making powerful technology safe and beneficial 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: $280,000 - $320,000 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.

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 Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact. Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. By joining the team you'll 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 - You’ll individually help deploy into production use cases with a considerable business impact across various industries. - You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. - You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning. - You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. - Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback 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 have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products - You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces. - You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases - You have deep understanding of concepts and algorithms underlying machine learning and LLMs - You have strong technical coding skills in Python - You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences Ideally you have: - Contributed to open-source projects in particular in the space of LLMs - Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager - You have experience with deep learning with Pytorch 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 .

S

Solution Architect, Metronome (AI Native)

Negotiable

Who we are About Stripe / Metronome Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. Metronome is the leading usage-based billing platform built for modern software companies. With Metronome, now a Stripe product, companies can launch products faster, offer any pricing model, and streamline finance workflows without writing code. Our platform computes hundreds of millions of invoices per billing period and continues to scale rapidly to accommodate new customers. We save them days of development time and manual invoicing, enabling them to use their billing data to better serve their customers. Our customers love our product and approach, and we’re humbled to work with amazing companies like OpenAI, Hubspot, NVIDIA, Confluent, Anthropic, and many others. You'll be joining an experienced team that includes founders who have successfully built and sold startups, alongside Stripes with direct experience scaling teams through hypergrowth at companies like Dropbox, Palantir, and MongoDB. You'll be joining Stripe and be part of the holistic Stripe platform approaching monetization. About the team The Solutions Engineering team at Metronome is a technical group that sits at the intersection of everything Metronome does: sales, account management, product, R&D, and operations. Bottom line, we own the technical side of the customer lifecycle from the very first discovery call through demos, POC, technical scoping, and handover to our post-sales groups. We act like a producer to get the show running with Metronome. This role will train you to grow across these vectors. What you’ll do The Metronome AI Native Solutions team operates at the intersection of technical sales, implementation, and customer success, purpose-built for the velocity and unique needs of AI-first companies. Unlike traditional sales engineering roles, this position owns the large parts of if not all of the deal cycle - from first call through technical win - and gets hands-on with implementation to ensure customers go live quickly. As an AI Native Solutions Architect in APAC, you'll be the primary technical owner for fast-moving AI companies operating in the Southeast Asia or China market, that may need to launch usage-based billing on tight timelines. This means: Owning the technical win: - Taking qualified inbound leads and driving them through discovery, demo, POC, and technical win - Using efficient discovery to quickly understand billing challenges, product launch timelines, and technical requirements - Bringing energy and urgency to every engagement—proactively driving deals forward, identifying blockers early, and building relationships across the customer organization (engineering, finance, product) to create champions - Running streamlined demos tailored to technical founders and product/engineering teams Driving hands-on implementation: - Providing customers with clear, actionable implementation plans to implement their usage-based billing launches - Writing code snippets, configuration examples, and integration guides to accelerate customer time-to-value - Pair programming or working alongside customer teams during POCs and initial setup - Designing up/downstream integrations into prospect systems with a bias toward pragmatic solutions that get them live quickly Building deep AI market expertise: - Building relationships with technical founders, engineering leaders, product, and finance teams at AI companies - Understanding the unique monetization challenges facing LLM providers, generative AI companies (image, video, audio), and AI tooling/wrapper companies and providing consultative guidance when prospects need direction on pricing and packaging strategy and implementation - Staying current on AI industry trends, pricing models, and competitive dynamics This role is perfect for someone who thrives in high-velocity environments, loves solving technical problems in real-time, and wants to be on the front lines of how AI companies monetize their products. Metronome directly influences how the next generation of AI infrastructure gets built—and our AI Native Solutions team drives this influence with our fastest-growing customer segment. The Metronome team still operates very much like a startup. As such, there's a lot still to figure out and tremendous room for high-agency, curious individuals to impact our direction and strategy, build processes from zero to one, and generally make a difference. If this excites you as much as it excites us, let's talk. Who you are This is roughly the set of things we’re looking for - if you’re interested in this role and don’t meet some of these on paper, err on the side of applying! Minimum requirements - 10+ years of experience in technical, customer-facing roles involving SaaS products (for example, sales engineering, solutions architecture, technical account management, implementation consulting) - Experience working with, at, or selling to AI companies - you understand how AI-first companies operate, their unique challenges, and the market landscape - Proven ability to own and drive customer-facing engagements and relationships independently - Strong technical aptitude with the ability to quickly learn new systems, write code snippets, and guide technical implementations - Experience working in high-velocity environments where speed-to-value matters and customers need to launch quickly - Excellent communication skills with technical buyers (engineers, product managers, technical founders) Preferred qualifications - Deep knowledge of the quote-to-cash space, including integrating with or otherwise interacting with tools like Salesforce, NetSuite, CPQs, etc. - Experience as a software engineer, product manager, or in other technical roles. - Experience in a pure sales role, particularly selling to technical buyers in engineering and product organizations or selling as a founding or early salesperson at a startup. - Familiarity and enthusiasm for AI developer tooling (Cursor, Lovable, Vercel, LangChain, etc.) and the broader AI infrastructure ecosystem - Professional fluency in Mandarin and English, as the role involves working with clients within the China market This role offers a unique opportunity to shape the future of AI monetization at one of the world's leading fintech companies. Join us in defining how the next generation of AI businesses will scale and succeed.

D

Staff Research Scientist - Foundation & World Mode...

Negotiable

As a Staff Research Scientist within Datadog AI Research ( DAIR ), you will drive fundamental research in foundation models and multimodality as a hands-on individual contributor. You will advance large-scale pre-training and multimodal learning across the diverse signals generated by distributed systems, including metrics, traces, logs, topology, and events. You will help set the technical direction for ambitious research programs, raise the technical bar for the researchers and research engineers around you, and collaborate with Datadog's product and engineering teams to translate research advances into products. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: - Drive research in foundation models and multimodal learning, shaping the technical direction for ambitious research programs grounded in observability and security - Own research problems end to end, from framing the question through experimentation, model development, and evaluation - Train large-scale multimodal models on diverse telemetry data, including metrics, logs, traces, topology, events, and other non-text modalities - Advance approaches to pre-training, representation learning, scaling, and evaluation for models that learn the dynamics of complex distributed systems - Collaborate with cross-functional teams across Research, Product, and Engineering to translate research advances into scalable Datadog capabilities - Share research findings with external audiences upon reaching significant project milestones. Who You Are: - You hold a PhD in Computer Science, Machine Learning, or a related field, or have equivalent experience, with deep expertise in areas such as foundation models, world models, multimodal learning, or generative modeling - You have driven technically ambitious research at meaningful scale as an individual contributor, whether in an industry research lab, startup, academic environment, or another research setting - You have extensive hands-on experience designing, training, or evaluating large-scale deep learning models (such as large language models), with experience in multimodal or non-text data considered a strong plus - You have a track record of research impact through influential publications, significant model or system contributions, widely used research artifacts, or equivalent technical achievements - You set technical direction through influence rather than authority, and you have mentored other researchers or engineers and elevated the quality of work around you - You want to stay deeply hands-on in research for the long term, and you can communicate complex research findings effectively across technical and non-technical audiences Datadog values people from all walks of life. We know not everyone will meet all the above qualifications on day one. That’s okay. If you’re passionate about technology and want to grow your experience, we encourage you to apply. LI-Hybrid About Datadog: Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram , LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog 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 other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form . This form is for accommodation requests only and cannot be used to inquire about the status of applications. Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice . For information on our AI policy, please visit Interviewing at Datadog AI Guidelines .

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Senior Systems Software Engineer - Machine Learnin...

Negotiable

NVIDIA has been transforming computer graphics, PC gaming, accelerated computing, and machine learning for more than 25 years. It’s a unique legacy of innovation fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing – an era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. We’re hiring a Deep Learning Engineer with strong experience in generative AI, LLMs/VLMs, computer vision, and agentic systems. If you’ve spent more time than you’d like to admit building workflows to populate data and/or diversify/expand your dataset, you’ll likely feel at home here. Bonus points if you’ve worked with 3D computer vision (extra bonus if you actually enjoyed it). The team is a balanced mix of engineers and scientists, and we care about both rigor and actually getting things out the door. The culture is collaborative, low-ego, and built around ownership. If you enjoy building systems that get used—and working with people who know when to debate and when to just run the experiment—this jobs is for you. What you will be doing: Convert research into real products (not just slide decks or notebooks) Help build workflows that diversify datasets and/or populate data Ship machine learning workflows/pipelines fast and iterate faster Leverage LLM/VLM and agents in the data generation pipeline Define evaluation criteria and run offline evals before any model or prompt change reaches production What we need to see: Masters degree (or equivalent experience) or preferably a PhD degree in Computer Science or a related field with 5+ years of experience Solid mathematical and algorithmic foundation and proven expertise demonstrated through research publications, internships, or significant project experience. Strong background in computer vision and deep learning. Excellent programming skills in Python and C/C++. Excellent software engineering fundamentals. Ability to develop code in Unix/Linux environments. Excellent written, visual, and verbal communication skills to present performance challenges, tradeoffs, and architectural alternatives. Strong collaboration skills to partner with other teams. Ways to stand out from the crowd: Experience designing and operating multi-agent pipelines in production, including handling non-deterministic failures, retry logic, and tool-call error recovery" Shipped a product feature backed by a VLM (e.g., image captioning, document understanding) — including handling inference latency, cost-per-call tradeoffs, and degraded-mode fallbacks Shipped AI-powered features to real users — not just prototyped with agent frameworks. If your experience is primarily personal projects or hackathons, this role may not be the right fit yet. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until November 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

U

Senior Machine learning engineer, AI Authoring

Negotiable

The opportunity Unity is building next-generation intelligence systems for gaming: systems that help AI-native teams understand the market and get the most out of the frontier models. We are hiring a Senior Machine Learning Engineer to lead this effort. You will own the end-to-end architecture, build pipelines, systems, and models, and scale a cross-disciplinary team of engine developers, game developers, and machine learning engineers. The work spans market forecasting, outcome prediction, multimodal content understanding, evaluation, and agentic systems. What you'll be doing Technical Excellence Work on our Game Intelligence ML platform, from data ingestion, semantic layer and feature stores through model registry, evaluation and serving. Make the calls that keep every model output reproducible and auditable: versioned data snapshots, model and prompt versions, and cost tracked per decision. Define, lead, and spearhead engineering practices for the agentic era, including agentic development workflows and evaluation methodologies. Partner with different functional teams and disciplines to translate expert human judgment into training signals. Shape the roadmap with the product team. Modeling Build predictors of commercial outcomes for games such as user acquisition cost, lifetime value and return on ad spend from large, noisy, multi-source signals. Build forecasting models over market signals that detect emerging demand and estimate when a window opens, peaks and closes. Deliver every prediction as a calibrated range with stated confidence, and own the ranking and portfolio logic that turns predictions into recommendations within a budget. Experimentation and agentic systems Design online experimentation with guardrails, safe exploration and clear human decision points. Build evaluation harnesses for LLM-based agents, including automated playtesting and multimodal assessment of generated content. Orchestrate frontier-model agents in production with strict data boundaries and cost control. Calibration and measurement Own the feedback loop that scores predictions against realized outcomes and corrects bias, coverage and signal weighting over time. Make the system report its own error in plain language so that creators and internal stakeholders can trust it. What we're looking for Passion for game industry Deep experience in Game, Game Engine development or Game publishing. Experience in machine learning with a track record of owning production ML systems or Agentic systems end to end, from data to serving to measured business outcome. Deep experience in performance marketing or ad-tech modeling: predicting acquisition cost, lifetime value, return on ad spend, retention or comparable outcomes. Strong grounding in probabilistic prediction and calibration: quantile or interval prediction, coverage, bias correction and backtesting of forecasts. Experience building LLM-based agent systems in production: orchestration, evaluation harnesses, prompt and model versioning, and cost control. Comfort building in a zero-to-one environment. You might also have Experience in mobile game user acquisition, LiveOps or monetization, on the studio or publisher side. Experience with Unity game engine, or with automated and bot-driven playtesting. Time-series and demand forecasting experience over noisy, multi-source market signals. Experience with the Claude Agent SDK, Codex or similar frameworks for multi-agent software production. Hands-on experience with BigQuery, ClickHouse, Kafka, Postgres, pgvector or their equivalents. Publications or open-source contributions in forecasting, causal inference, calibration or agentic systems. This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate’s relevant experience, professional background, and skill set. Benefits At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance. Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status. While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program Life at Unity Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com . Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know. This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English. This posting is intended to fill an existing vacancy, and we are committed to providing applicants with updates throughout the hiring process in accordance with applicable law. Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity. Your privacy is important to us. Please take a moment to review our Prospect and Applicant Privacy Policies. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

M

Account Executive, Digital Natives

Negotiable

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 our Account Executive, Digital Natives, you will grow Mistral's business with companies building AI-native products across the UK and Northern Europe. These are engineering-led companies whose products run on models: coding tools, voice agents, document automation, customer support platforms, search, and more. Their buyers are founders, CTOs, and AI engineering leads, and they choose models on performance, cost, reliability, and data residency. You will be the first member of the Digital Natives team based in Europe. You will own deals end to end, from first conversation through production launch and expansion, working alongside our solutions engineering, product, science, and legal teams. This role is based in London, with regular travel across the region and to our Paris headquarters. What You Will Do: Pipeline development (targeted outbound and qualified inbound): - Identify and engage the most promising AI-native companies in your territory, and build relationships with the founders and engineering leaders who select models - Qualify and convert inbound interest from teams already building on our API into commercial relationships Technical evaluation: - Guide customers through evaluations of our models on their real workloads, working with our solutions engineers to keep the process fast and the results clear - Turn successful evaluations into production usage and long-term commercial agreements Deal management and closing: - Own the commercial cycle end to end: qualification, evaluation, negotiation, and close, together with our legal and solutions teams - Manage deals with multiple technical and executive stakeholders on both sides, and keep everyone aligned on timelines and next steps Account growth: - Grow usage within existing customers as they ship new products and features on our models - Stay close to customers' roadmaps so Mistral is positioned for their next workload before it reaches production Working with product and science: - Bring customer feedback, usage patterns, and competitive insight back to our product and science teams to inform priorities and the roadmap - Connect customers directly with our product and research teams where it accelerates their success What We're Looking For: - 5 to 8 years of sales experience, with a track record of closing deals with startups and scale-ups for a technical product (API, developer tools, infrastructure, or data) - Experience selling to technical buyers: founders, CTOs, and engineering leaders - Working knowledge of how AI products are built, and the ability to hold a credible conversation about models, evaluation, and deployment with an engineering audience - Experience at a fast-growing startup, ideally in AI, developer tools, or infrastructure - Comfort with usage-based revenue, where growth comes from what customers ship rather than from a single contract - Excellent English; French, German, Dutch, or a Nordic language is a plus - Strong negotiation and communication skills, and a hands-on, low-ego approach 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 .

O

Head of UK, Ad Solutions

Negotiable

About the Team OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity. In support of that mission, the Ads Solutions team partners closely with advertisers, agencies and strategic partners to help businesses unlock value through AI-powered advertising solutions while maintaining strong standards for user trust, platform integrity and responsible innovation. As OpenAI’s advertising business continues to scale, the Head of UK will play a critical role in growing the UK business, building strategic advertiser and agency relationships, and developing a high-performing commercial team. You will work closely with EMEA and global leadership to translate OpenAI’s advertising strategy into a clear plan for the UK market. About the Role We are seeking a Head of UK, Ad Solutions to lead and scale OpenAI’s advertising business in the United Kingdom. Based in London, you will lead a team of Client Partners and Customer Success Managers supporting UK advertisers and agencies, with responsibility for country strategy, revenue performance and advertiser success. This is a strategic and hands-on leadership role. You will identify the sectors, customers and partnerships that offer the greatest opportunity for sustainable growth, build executive-level relationships across the UK advertising industry, and establish the operating discipline needed to deliver ambitious commercial goals. You will partner closely with Product, Engineering, Marketing, Operations and Policy teams to ensure UK advertiser needs inform product development and go-to-market decisions. Working alongside regional and global account teams, you will also help UK-based advertisers and agencies grow their international activity through coordinated account plans. The ideal candidate combines deep knowledge of the UK advertising market with strong people leadership, commercial judgement and operational rigour. You are equally comfortable coaching a team, engaging a CMO or agency leader, solving customer challenges and building a business in a fast-moving environment. In this role, you will: - Own the UK commercial strategy, revenue goals and business performance, translating regional priorities into clear plans and accountable execution. - Recruit, lead, coach and develop a team of Client Partners and Customer Success Managers, building a high-performance, inclusive and customer-focused culture. - Prioritise UK sectors, advertiser segments and strategic accounts, allocating resources to accelerate adoption, retention and sustainable revenue growth. - Build and maintain executive-level relationships with leading UK advertisers, agency holding companies, independent agencies and strategic partners. - Develop agency and technology partnerships that expand advertiser access, improve customer outcomes and support a scalable UK business. - Partner with sales and customer success teams to strengthen the full advertiser lifecycle, from onboarding and campaign activation to measurement, renewal and expansion. - Drive forecasting, pipeline management, account and territory planning, and business reviews to improve execution and revenue predictability. - Help advertisers define success and build evidence-based investment cases, using campaign performance and measurement insights to guide growth. - Represent the voice of UK advertisers and agencies internally, translating customer feedback and market insights into actionable input for Product, Engineering and leadership teams. - Coordinate with EMEA and global teams on international customer opportunities, product launches and shared account strategies. - Partner with Policy, Legal and other relevant teams to support responsible market growth, strong platform integrity and user trust. - Establish repeatable processes and playbooks, and represent OpenAI’s advertising offering at industry events and in senior customer and partner discussions. You might thrive in this role if you: - Have significant experience in digital advertising, media or technology, with a strong track record in senior commercial leadership. - Have experience leading high-performing sales, account management, customer success or revenue teams, including hiring and developing exceptional talent. - Have a proven record of exceeding revenue targets and building or scaling an advertising business in the UK. - Bring deep knowledge of the UK advertising ecosystem, including major advertisers, agency holding companies, independent agencies and technology partners. - Can build trusted relationships with C-suite executives and agency leaders, and personally influence complex, strategic commercial opportunities. - Combine strategic thinking with hands-on execution, sound judgement and strong operational discipline. - Understand digital advertising products, performance measurement and the commercial needs of both brand and performance advertisers. - Are highly data-driven and use analytics to prioritise opportunities, assess customer outcomes and drive accountability. - Work effectively across functions and geographies, aligning local priorities with regional and global goals. - Thrive in ambiguity and enjoy building teams, processes and new commercial opportunities from the ground up. - Are excited by the possibilities of AI in marketing and committed to helping advertisers adopt transformative technologies responsibly. 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.

O

Head of Agency, EMEA - Ad Solutions

Negotiable

About the Team OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity. In support of that mission, the Ads Solutions team partners closely with advertisers, agencies and strategic partners to help businesses unlock value through AI-powered advertising solutions while maintaining strong standards for user trust, platform integrity and responsible innovation. As OpenAI’s advertising business continues to scale globally, the Head of Agency, EMEA will play a critical role in developing strategic agency partnerships, accelerating advertiser adoption and shaping how agencies help their clients succeed with OpenAI. You will work closely with EMEA and global leadership to translate our advertising strategy into a clear plan for the region’s agency ecosystem. About the Role We are seeking an Head of Agency, EMEA - Ad Solutions to lead and scale OpenAI’s agency partnerships across Europe, the Middle East and Africa. You will own the regional agency strategy, building relationships with agency holding companies, their networks and leading independent agencies to drive sustainable revenue growth and advertiser success. This role is based in London and reports to the Head of Ads Solutions for EMEA. This is a highly strategic and hands-on leadership role. You will engage senior agency executives, develop joint business plans and commercial partnerships, and work with country sales and customer success teams to turn regional agreements into meaningful local execution. You will help agencies build the knowledge, capabilities and confidence to incorporate OpenAI’s advertising solutions into their clients’ marketing strategies. You will partner closely with Product, Engineering, Marketing, Operations and Policy teams to ensure agency and advertiser feedback informs product development and go-to-market decisions. Working alongside global agency teams, you will align international partnerships with the needs of EMEA markets and help establish scalable ways of working across the region. The ideal candidate combines deep knowledge of the EMEA agency landscape with strong commercial judgement, executive influence and operational rigour. You are equally comfortable negotiating a strategic partnership, working with local teams to unlock client opportunities, and helping agency leaders understand the possibilities of AI-powered advertising. In this role, you will: - Develop and execute OpenAI’s EMEA agency strategy, prioritising partnerships, markets and growth opportunities across agency holding companies, networks and independent agencies. - Own agency partnership revenue goals and business performance, working with country leaders to establish clear targets, accountabilities and execution plans. - Build and maintain executive-level relationships with agency leaders across management, investment, trading, strategy, planning, activation, data and measurement. - Develop joint business plans that connect agency priorities with advertiser outcomes, with clear commitments, milestones and measures of success. - Lead the development and negotiation of regional trading agreements and strategic commercial partnerships, working closely with Finance, Legal and regional leadership. - Translate regional and global agency agreements into local activation, coordinating with country sales and customer success teams on account plans, advertiser onboarding and growth. - Expand the number of agency clients advertising with OpenAI and deepen adoption across relevant products and use cases. - Partner with Marketing and customer-facing teams to deliver agency education, leadership engagement and enablement programmes that build lasting capability across planning and buying teams. - Establish a disciplined operating cadence for pipeline management, forecasting, partnership reviews and tracking delivery against commercial commitments. - Define clear ways of working across agency, direct advertiser, country and global account teams to coordinate customer engagement and support shared growth. - Bring agency and advertiser insights to Product, Engineering and leadership teams, helping identify opportunities to improve the customer experience, measurement and product adoption. - Provide strategic direction and coaching to colleagues working on agency partnerships across EMEA, building shared playbooks and consistently high standards of execution. - Represent OpenAI’s advertising offering in senior agency discussions and industry forums, maintaining a strong commitment to user trust and responsible innovation. You might thrive in this role if you: - Have 15+ years of experience in the advertising industry, including significant experience in agency partnerships, digital advertising sales or senior agency leadership. - Have a proven track record of exceeding revenue targets and building strategic agency partnerships across multiple EMEA markets. - Bring deep knowledge of the EMEA agency ecosystem and established senior relationships across agency holding companies, networks and independent agencies. - Have experience developing and negotiating complex trading agreements, joint business plans and multi-market commercial partnerships, and translating them into measurable results. - Understand how agency investment decisions are made and can build relationships across executive leadership, trading, planning, activation, data and measurement teams. - Can articulate a compelling business case for a new advertising platform, connecting brand and performance objectives with relevant products and credible measurement. - Combine strong strategic thinking with a bias towards execution, operational excellence and personal accountability. - Are highly data-driven and comfortable using analytics to prioritise investment, assess partnership performance and identify opportunities for growth. - Have experience leading complex initiatives across distributed teams and influencing senior stakeholders without relying on direct reporting relationships. - Enjoy coaching and developing colleagues, sharing expertise and helping teams build effective agency partnerships. - Thrive in ambiguous, fast-changing environments and enjoy building new commercial models, processes and partnerships from the ground up. - Are passionate about AI and excited by the opportunity to shape how agencies and advertisers adopt transformative technologies responsibly at scale. 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.

O

Customer Success Manager, Ads Solutions

Negotiable

About the team OpenAI’s mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Sales team partners closely with customers to deeply understand their businesses and needs, helping inform the development of products and solutions that drive meaningful revenue growth and long-term success on the platform—while maintaining strong standards for user trust and platform integrity. About the role We’re looking for a Customer Success Manager to support advertisers in onboarding, launching, and growing on OpenAI’s advertising platform. You will manage a portfolio of partners and serve as a trusted advisor, helping them achieve their business objectives while ensuring a strong and responsible experience on our platform. This role sits at the intersection of relationship management, strategy, and execution. You’ll work closely with Sales to drive long-term partner growth and with internal teams to continuously improve the advertiser experience. In this role, you’ll: - Own relationships with a portfolio of advertising partners, serving as their primary point of contact. - Guide advertisers through onboarding and campaign launches to ensure strong adoption of OpenAI’s ads products. - Analyze campaign performance and provide clear, actionable recommendations to improve outcomes. - Identify opportunities to expand partnerships through increased product adoption and incremental investment. - Partner cross-functionally with Sales, Product, Analytics, Policy, and Operations to resolve issues and enhance platform value. - Surface advertiser feedback and insights to inform product improvements and long-term strategy. - Help build scalable processes and best practices that support the growth of OpenAI’s advertising ecosystem. You might thrive in this role if you: - Have 5-10+ years of experience in digital advertising, account management, customer success, consulting or a related client-facing role. - Have experience managing advertiser or agency relationships in a platform, publisher, or adtech environment. - Are comfortable interpreting performance data and translating insights into strategic recommendations. - Have experience with data querying (e.g. SQL, advanced excel/GSheet) - Communicate clearly and builds trust with both technical and non-technical stakeholders. - Operate with ownership and accountability in fast-moving, evolving environments. - Demonstrate sound judgment and a commitment to user trust and responsible platform growth. 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.

F

Customer Trust Specialist

$190,000 – $210,000

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 own the customer-facing side of our trust program. Where our GRC team keeps the compliance engine running behind the scenes, you'll be the one customers actually interact with, turning our security, privacy, and AI-governance posture into answers that earn and keep trust. You'll own security questionnaires end to end, drive our trust automation platform, and represent the program on customer calls and in contract negotiations. This is a great fit for someone who knows the security-review process cold and wants to shape how a scaling AI company answers for its controls. What you'll do - Own security questionnaires end to end: intake, scoping, drafting, review, and delivery for customer security assessments, RFPs, and vendor evaluations across our enterprise pipeline, in whatever format they arrive (OneTrust, spreadsheets, portals, email). - Run our trust automation platform: operate and improve the system that generates answers from our governed knowledge base, with deterministic guardrails that enforce accuracy, protect confidentiality, and never over-claim. You'll judge answer quality, tune retrieval, and keep the guardrails honest. - Maintain the knowledge base as a living source of truth: keep answers current as the platform, contracts, certifications, and our control environment evolve; ingest new evidence (SOC 2, ISO 27001/27701/42001, HIPAA, penetration tests); and retire 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 does not fit a questionnaire but still shapes a customer's confidence. - Join customer calls: represent the security and trust program on prospect and customer calls, fielding architecture, privacy, and AI-safety questions alongside Sales and Solutions; partner closely with the sales team from intake through close, so security and trust are embedded in the deal rather than a last-mile gate. - Partner on contracts: work with Legal and Deal Desk on security, privacy, and AI terms in DPAs and MSAs; translate between a customer's redline and what our controls actually say; know which positions are standard and which need escalation. - Keep the program honest: apply 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 before it leaves the building. - Turn program data into action: track where the knowledge base gaps are, which questions we cannot yet answer well, and where automation is saving or costing time, and report that to leadership. - Curate and maintain our public security and trust artifacts: keep the Trust Center, security whitepapers (including the Model Security and Safety Assurance whitepaper), and supporting evidence current and aligned with what we actually do; you are responsible for the external-facing story, not just the internal record behind it. How the role will grow As you build context on our platform and customers, you'll take on broader ownership of the trust program: - Program growth: shape the direction of trust automation, where the engine should answer next, which frameworks and AI-assurance standards (ISO 42001, NIST AI RMF, EU AI Act) the knowledge base needs to cover, and how the program scales with deal volume. - Cross-functional influence: work with Product, Engineering, Legal, and Sales to make our security and AI-safety posture a genuine differentiator rather than a checkbox. - Mentorship: set the bar for answer quality and rigor for the team, and help build the playbook for how Fireworks earns customer trust as we grow. What we're looking for - 5 to 7 years of experience in customer-facing security, trust, or GRC roles: security assurance, customer trust, vendor security review, sales engineering with a security focus, or similar. - Deep familiarity with security questionnaires and the customer security-review process, across formats (CAIQ, SIG, custom spreadsheets, OneTrust and similar portals) and frameworks (SOC 2, ISO 27001/27701/42001, HIPAA, GDPR, NIST). - Comfort reading and discussing contracts (DPAs, MSAs, BAAs) and translating between a customer's legal language and a company's actual security posture. - Strong written communication; you can turn a control requirement into a clear, accurate answer a customer trusts, and you know the difference between answering a question and over-answering it. - Comfort with cloud environments (AWS, GCP, or Azure) and SaaS architectures; you can discuss multi-tenancy, isolation, encryption, and data flows credibly with a technical buyer. - Experience with or strong interest in trust-automation and AI-assisted tooling; you are excited about a program that uses its own platform to answer for itself, and you understand 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, not just plausible. - A collaborative, low-ego approach; you work across Legal, Sales, Engineering, and Security as a partner, and you know when to escalate rather than answer. - Bonus: familiarity with AI/ML platforms, LLM inference, or AI governance concepts (model training data, 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.

E

Senior AI Programmer

Negotiable

WHAT MAKES US EPIC? At the core of Epic’s success are talented, passionate people. Epic prides itself on creating a collaborative, welcoming, and creative environment. Whether it’s building award-winning games or crafting engine technology that enables others to make visually stunning interactive experiences, we’re always innovating. Being Epic means being a part of a team that continually strives to do right by our community and users. We’re constantly innovating to raise the bar of engine and game development. PROGRAMMING - UNREAL ENGINE What We Do Unreal-powered projects have been on the bleeding edge of real-time entertainment for over 20 years. Our team of programming experts are always innovating to improve the tools and technology that empower content developers worldwide. What You'll Do Epic Games is seeking an experienced Senior Al Programmer to join our Unreal Engine (UE) NPC team, which owns the core NPC technology (behavior, perception, navigation, in-game generative Al, etc.) that powers characters in UE, Fortnite, and UEFN. You'll work on the systems every UE and UEFN developer relies on to bring NPCs to life. In this role, you will - Extend, evolve, and maintain UE's NPC systems, including behavior, perception, and navigation - Design and present new technical design and APIs for NPC systems used by developers worldwide - Evaluate and experiment with in-game generative AI features in close collaboration with Epic's ML research groups - Optimize performance, memory usage, and scalability of NPC systems across UE What we're looking for - Shipped AAA titles with hands-on experience building AI systems (behavior trees, perception, pathfinding, etc.) - Professional experience with UE, preferably in system design - Strong C++ skills and the ability to code and design core AI technologies - Excellent communication and collaboration skills, with the ability to work autonomously - Experience integrating LLMs or other generative models into real-time applications is a plus - Experience using AI coding assistants (e.g. Claude Code) to improve development efficiency is a plus - Live-service game experience is a plus This role is open to multiple locations in North America (including CA & WA). Pay Transparency Information The expected annual base pay range(s) for this position are detailed below. Each base pay range is relevant only for individuals who are residents of or will be expected to work within the specified locale. Compensation varies based on a variety of factors, which include (but aren’t limited to) things such as skills and competencies, qualifications, knowledge, and experience. In addition to base pay, most employees are eligible to participate in Epic’s generous benefit plans and discretionary incentive programs (subject to the terms of those plans or programs). California Base Pay Range $190,010 - $278,682 USD Washington Base Pay Range $172,736 - $253,347 USD ABOUT US Epic Games is a leading interactive entertainment company. For over 30 years we've been making award-winning games and engine technology that empowers others to make visually stunning games and 3D content that bring environments to life like never before. Epic's award-winning Unreal Engine technology not only provides game developers the ability to build high-fidelity, interactive experiences for PC, console, mobile, and VR, it is also a tool being embraced by content creators across a variety of industries such as media and entertainment, automotive, and architectural design. As we continue to build our Engine technology and develop remarkable games, we strive to build teams of world-class talent. Like what you hear? Come be a part of something Epic! Epic Games deeply values diverse teams and an inclusive work culture, and we are proud to be an Equal Opportunity employer. Learn more about our Equal Employment Opportunity (EEO) Policy here . Note to Recruitment Agencies: Epic does not accept any unsolicited resumes or approaches from any unauthorized third party (including recruitment or placement agencies) (i.e., a third party with whom we do not have a negotiated and validly executed agreement). We will not pay any fees to any unauthorized third party. Further details on these matters can be found here .

R

Product Manager, AI Foundations

Negotiable

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . About the Team: We build the shared ML and AI capabilities that power experiences across our consumer products. Our work spans the platform that enables teams to develop, evaluate, and deploy models, and the intelligence that helps those models understand content, people, and communities. We partner with consumer product teams and infrastructure engineering to turn advances in ML and AI into reusable capabilities that improve discovery, personalization, and other consumer experiences. About the Role: We’re looking for a senior individual contributor to lead product strategy across ML Platform and ML Understanding. Reporting to Consumer product leadership, you’ll shape the foundations that help teams build better products: from reliable, efficient model development and deployment to richer classifications and representations of content and users. This role combines technical depth, consumer product judgment, and organizational influence. You’ll connect needs across applications, identify the investments with the greatest shared value, and align product and engineering leaders around a coherent strategy with measurable outcomes. What You'll Do: - Set the strategy for shared AI foundations. Define a multiyear vision and prioritized roadmap spanning ML platform capabilities and content and user understanding. - Connect foundational investments to consumer outcomes. Translate needs across recommendations, search, discovery, and emerging AI experiences into clear requirements and investment priorities. - Advance content and user understanding. Guide investments in classification, taxonomies, embeddings, multimodal understanding, and representations of user interests and intent. - Improve the ML development lifecycle. Partner with engineering on capabilities for data and feature access, training, inference, evaluation, deployment, and monitoring. - Make shared capabilities useful and widely adopted. Establish clear interfaces, onboarding paths, and feedback mechanisms that help application teams build on common foundations. - Lead investment and technical tradeoffs. Align senior partners on sequencing, dependencies, and decisions involving model quality, flexibility, reliability, latency, and cost. - Define and demonstrate success. Measure platform adoption, development velocity, model and representation quality, operational efficiency, and downstream improvements in consumer experiences. What We're Looking For: - A track record of leading complex ML or AI products, with experience in shared platforms, recommendation systems, search, or related technical domains. - Strong technical fluency across the ML lifecycle and the ability to engage deeply with engineering and applied science partners on architecture and investment decisions. - Experience with content understanding, classification, embeddings, or user representations, and an understanding of how their quality affects consumer products. - Product judgment that connects foundational capabilities to concrete user needs, adoption, and measurable business impact. - Demonstrated ability to establish direction across multiple teams, resolve competing priorities, and influence senior leaders without direct authority. - Comfort defining strategy in ambiguous spaces while maintaining clear priorities, credible execution plans, and accountability for outcomes. - Sound judgment about evaluation, data quality, privacy, and the responsible use of content and user signals. Benefits: - Comprehensive Healthcare Benefits and Income Replacement Programs - 401k with Employer Match - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $260,800 - $365,100 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

F

Applied Data Researcher

Negotiable

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma is building the system of record for digital product development: collaborative tools with natural interfaces that bring PMs, developers, QA, and designers together. That creates new-to-the-world problems in how we build AI products, understand how people use them, and evaluate what makes them useful. You'll work with a unique, petabyte-scale dataset with rich traces of collaborative design and product building to tackle those problems. We're looking for an Applied Data Researcher who combines scientific depth with a proactive builder mindset. Reporting directly to our Head of Data, with regular visibility with C-level executives, you'll identify and vet opportunities, lead investigations into critical questions, and build useful Data products, tools, and prototypes. You'll work across Data Science, Engineering, Product, Design, and AI Research, building directly and providing technical direction to teams of other scientists as efforts grow. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: - Identify and vet consequential opportunities across Data products and tools, AI measurement and evaluation, and applied data capabilities; lead investigations and shape priorities with partners - Develop and validate methods for evaluating generative AI and agentic workflows, including representative datasets, baselines, rubrics, and evals; investigate uncertainty, bias, failure modes, and real user outcomes - Personally write code and build or adapt LLM-powered tools, agentic workflows, models, prototypes, and demos that test scientific, product, and tool hypotheses, using AI-assisted coding and analysis in your work - Provide technical direction and oversight for larger projects, delegate work to teams of senior and staff scientists, and mentor scientists and engineers while maintaining a substantial personal contribution to code and methods - Independently drive delivery or partner with engineering to turn useful prototypes into maintained systems, balancing quality, latency, cost, reliability, and iteration speed - Establish reusable methods, tools, and technical standards; iterate with users, drive adoption across teams, and use evidence to improve an approach or recommend a change in direction - Communicate findings, recommendations, limitations, and tradeoffs clearly to partners and C-level executives, connecting scientific and technical work to important product and company decisions We'd love to hear from you if you have: - Deep expertise in machine learning, statistics, causal inference, or a related quantitative field, plus hands-on experience in generative AI evaluation and measurement, including evals, labeling, and agentic workflows - Fluent programming skills in Python or a comparable language, plus SQL, and a record of independently building, debugging, testing, and reviewing useful software, including working effectively with AI-assisted development tools - A proactive builder mindset and end-to-end ownership: experience identifying important opportunities and carrying ambiguous work through method development, implementation, rigorous evaluation, and sustained use by others - A sustained record of company-, organization-, or cross-pillar scientific impact, including shaping technical direction, overseeing larger projects, and leading other senior scientists through influence and delegation - Strong judgment, independence, and collaborative communication, including experience making recommendations to C-level executives, explaining uncertainty and tradeoffs, and aligning partners on priorities and decisions While it's not required, it's an added plus if you also have: - Experience with human labeling, automated judge validation, conversational data, or multimodal AI and machine learning - Experience building interactive applications, lightweight interfaces, APIs, or reusable open-source tools - Cloud and data infrastructure experience; familiarity with Snowflake, AWS, Dagster, dbt, or Hex is useful, but no particular vendor or framework is required - An MS or PhD in machine learning, computer science, statistics, or a similar quantitative discipline; graduate research, publications, or equivalent applied depth At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you're excited about this role but your past experience doesn't align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. Figma offers equity to employees, as well as a competitive package of additional benefits, including health, dental, and vision coverage; retirement benefits with company contributions; parental leave and reproductive or family planning support; mental health and wellness benefits; and paid time off. Figma provides paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws, including the requirements of the Washington Minimum Wage Act and related regulations. Exempt employees are eligible for employer‑provided paid flexible PTO in addition to flexible paid sick leave. PTO is subject to manager approval. Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts. Figma also offers sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles. All compensation and benefits are subject to applicable plan terms and may be modified by Figma at any time, consistent with applicable law. Annual Base Salary Range: $235,000 - $376,000 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status , or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: - Holding interviews in an accessible location - Enabling closed captioning on video conferencing - Ensuring all written communication be compatible with screen readers - Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: - Candidates may submit up to 5 applications during any rolling 30-day period. - Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.

C

Senior Response Engineer - Cloudflare Managed Defe...

Negotiable

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Location: Singapore About the Department Cloudforce One is Cloudflare's threat operations and research team, responsible for identifying and disrupting cyber threats ranging from sophisticated cyber criminal activity to nation-state sponsored advanced persistent threats (APTs). Cloudforce One works in close partnership with external organizations and internal Cloudflare teams, continuously developing operational tradecraft and expanding ever-growing sources of threat intelligence to enable expedited threat hunting and remediation. Members of Cloudforce One are at the helm of leveraging an incredibly vast and varied set of data points that only one of the world's largest global networks can provide. The team analyzes these unique data points at massive scale and efficiency, synthesizing findings into actionable threat intelligence to better protect our customers. About INTERDICT I.N.T.E.R.D.I.C.T. (Identify, Neutralize, Triage, Engage, Respond, Disrupt, Integrate, Contain, Threat Hunting) is Cloudforce One's unified operational security organization responsible for identifying, analyzing, and responding to threats targeting Cloudflare and its customers. INTERDICT encompasses three main sub-functions: - Cloudflare Managed Defense (CMD): Network and application security monitoring for 'Under Attack' mitigation support. - PhishGuard: Managed email threat detection and response service. - Detection Engineering: ML model development and detection optimization. Together, INTERDICT provides comprehensive 24×7×365 protection across email, application, and network threat surfaces. Role Summary As a Senior Response Engineer within the Cloudflare Managed Defense Center (CMDC), you will serve as a subject-matter expert and technical escalation point for threat mitigation across Cloudflare’s strategic enterprise customer base. In this role, you will lead the response to sophisticated, multi-vector cyberattacks spanning OSI Layers 3, 4, and 7, operating beyond standard playbooks to diagnose anomalies, engineer custom mitigations, and stabilize mission-critical infrastructure under fire. Beyond active incident command, you will act as a force multiplier: architecting customer-specific defense strategies, authoring and refining automated detection logic, mentoring Tier 1 and Tier 2 engineers, and collaborating directly with Cloudflare Product and Engineering teams. We are looking for an experienced, high-ownership technical leader who excels during high-stakes incidents and is passionate about mentoring others while advancing threat mitigation at scale. CMDC operates 24×7×365. This role participates in a regional shift rotation and on-call escalation rota including periodic weekend and public-holiday coverage as part of a follow-the-sun model across AMER, EMEA, and APAC. Role Responsibilities - Act as the technical lead and incident commander during high-impact, multi-vector security events, designing and deploying bespoke mitigation strategies when standard runbooks do not suffice. - Perform deep-dive forensic analysis into complex Layer 3/4 and Layer 7 traffic anomalies, identifying zero-day attack patterns, sophisticated bot networks, and novel evasion techniques. - Apply advanced mitigation strategies and filter malicious traffic using Cloudflare’s core security suite, including Magic Transit, Web Application Firewall (WAF), and Advanced Rate Limiting. - Lead technical communications and incident bridge calls with enterprise C-level executives, principal network engineers, and security teams during critical events, clearly articulating root causes, impact assessments, and remediation paths. - Monitor and investigate proactive security alerts across internal telemetry systems to rapidly triage incoming events, assess blast radius, and validate threat severity. - Adhere to and champion strict customer SLAs for alert response times, event analysis, and clear executive reporting. - Mentor and elevate Tier 1 and Tier 2 engineers through structured shadowing, technical post-mortems, and internal training. - Partner with internal Engineering and Product teams to translate operational attack trends into prioritized platform enhancements, tool feedback, and automated detection logic. Role Requirements (Must-Have Skills) - A minimum of 6–8 years of hands-on experience in a high-volume Security Operations Center (SOC), Managed Detection and Response (MDR), network engineering, or incident response environment dealing directly with live threat mitigation. - Comprehensive knowledge of networking principles and internet infrastructure, including TCP/IP, UDP, ICMP, DNS, BGP routing mechanics, and edge network design. - Deep expertise in Layer 7 protocols and web architectures (HTTP/1.1, HTTP/2, HTTP/3, TLS handshakes/ciphers, reverse proxy models, and API security). - Experience analyzing network traffic data for anomaly detection and designing, tuning, and executing advanced mitigation strategies against L3/L4 and L7 attacks, including bespoke countermeasures when standard playbooks are insufficient. - Advanced proficiency in packet capture and network traffic analysis using tools such as tcpdump, Wireshark, or tshark to isolate anomalies and dissect malformed or novel payloads. - Practical experience analyzing and mitigating security incidents using AI and machine learning tools, paired with the hands-on capability to build and integrate custom tooling that improves operational workflows, accelerates log telemetry analysis, and defends against AI-driven botnets and adversarial edge attacks. - Proficiency in using the command line (Bash shell) alongside general system administration literacy across Linux, Mac, or Windows environments. - Proven experience commanding incident bridges, making decisive risk-tradeoff decisions, and maintaining composure while managing enterprise stakeholders during high-pressure crises. Nice-to-Have Skills - Direct experience querying large-scale distributed logging and analytics systems using SQL, GraphQL, ClickHouse, or SIEM platforms (Splunk, Elastic, Sumo Logic). - Hands-on experience defending against advanced persistent threats (APTs), credential stuffing, scraping botnets, or application-layer bypass attacks against major CDNs/WAFs. - Relevant industry certifications, such as CISSP, CCNP/CCIE, or advanced GIAC credentials (e.g., GCIA, GCIH, GNFA). What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs. More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer. We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness. All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

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Senior AI Programmer

Negotiable

WHAT MAKES US EPIC? At the core of Epic’s success are talented, passionate people. Epic prides itself on creating a collaborative, welcoming, and creative environment. Whether it’s building award-winning games or crafting engine technology that enables others to make visually stunning interactive experiences, we’re always innovating. Being Epic means being a part of a team that continually strives to do right by our community and users. We’re constantly innovating to raise the bar of engine and game development. ENGINEERING - UNREAL ENGINE What We Do Unreal-powered projects have been on the bleeding edge of real-time entertainment for over 20 years. Our team of engineering experts are always innovating to improve the tools and technology that empower content developers worldwide. What You'll Do Epic Games is seeking an experienced Senior Al Programmer to join our Unreal Engine (UE) NPC team, which owns the core NPC technology (behavior, perception, navigation, in-game generative Al, etc.) that powers characters in UE, Fortnite, and UEFN. You'll work on the systems every UE and UEFN developer relies on to bring NPCs to life. In this role, you will - Extend, evolve, and maintain UE's NPC systems, including behavior, perception, and navigation - Design and present new technical design and APIs for NPC systems used by developers worldwide - Evaluate and experiment with in-game generative AI features in close collaboration with Epic's ML research groups - Optimize performance, memory usage, and scalability of NPC systems across UE What we're looking for - Shipped AAA titles with hands-on experience building AI systems (behavior trees, perception, pathfinding, etc.) - Professional experience with UE, preferably in system design - Strong C++ skills and the ability to code and design core AI technologies - Excellent communication and collaboration skills, with the ability to work autonomously - Experience integrating LLMs or other generative models into real-time applications is a plus - Experience using AI coding assistants (e.g. Claude Code) to improve development efficiency is a plus - Live-service game experience is a plus EPIC JOB + EPIC BENEFITS = EPIC LIFE Our intent is to cover all things that are medically necessary and improve the quality of life. We pay 100% of the premiums for both you and your dependents. Our coverage includes Medical, Dental, a Vision HRA, Long Term Disability, Life Insurance & a 401k with competitive match. We also offer a robust mental well-being program through Modern Health, which provides free therapy and coaching for employees & dependents. Throughout the year we celebrate our employees with events and company-wide paid breaks. We offer unlimited PTO and sick time and recognize individuals for 7 years of employment with a paid sabbatical. ABOUT US Epic Games is a leading interactive entertainment company. For over 30 years we've been making award-winning games and engine technology that empowers others to make visually stunning games and 3D content that bring environments to life like never before. Epic's award-winning Unreal Engine technology not only provides game developers the ability to build high-fidelity, interactive experiences for PC, console, mobile, and VR, it is also a tool being embraced by content creators across a variety of industries such as media and entertainment, automotive, and architectural design. As we continue to build our Engine technology and develop remarkable games, we strive to build teams of world-class talent. Like what you hear? Come be a part of something Epic! Epic Games deeply values diverse teams and an inclusive work culture, and we are proud to be an Equal Opportunity employer. Learn more about our Equal Employment Opportunity (EEO) Policy here . Note to Recruitment Agencies: Epic does not accept any unsolicited resumes or approaches from any unauthorized third party (including recruitment or placement agencies) (i.e., a third party with whom we do not have a negotiated and validly executed agreement). We will not pay any fees to any unauthorized third party. Further details on these matters can be found here .

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Member of Technical Staff (Web Access Engineer, Cr...

Negotiable

Perplexity is hiring a Web Access Engineer for the Crawler team to build reliable fetching and rendering systems for AI-powered search. You'll work on freely available public web content, within site permissions and approved access policies, and develop the infrastructure that supplies content to downstream indexing and retrieval systems. Your focus will be diagnosing network errors, page-loading issues, and incomplete rendering. You'll trace problems from network protocols through client-side execution, distinguish technical failures from intentional access restrictions, and turn findings into production fixes that improve content quality and efficiency at scale. Responsibilities - Own fetching and rendering improvements end to end, from investigation through implementation and production rollout, partnering with crawler engineers and SREs. - Investigate fetch and rendering failures across DNS, TLS, HTTP, caching, redirects, and client-side rendering, and classify root causes. - Improve page loading, completion detection, and content capture to preserve relevant content and handle dynamic pages reliably. - Ensure the crawler respects site-imposed access restrictions and rate limits, identifies itself clearly, and retries only transient technical errors. - Build tools to reproduce failures, compare crawler output against expected page content, and turn findings into regression tests. - Define metrics for fetching reliability, content completeness, and error classification, and use them to prioritize improvements. Qualifications - 5+ years of software engineering experience in web infrastructure, browsers, CDNs, or crawling, with strong programming skills in at least one of Go, Python, Rust, or C++. - Deep understanding of HTTP/1.1, HTTP/2, and HTTP/3, including status semantics, caching, conditional requests, content encoding, and redirects; strong knowledge of TLS, DNS, cookies, and sessions. - Understanding of CDN caching and content delivery, HTTP error handling, retry backoff, and server-defined rate limits. - Knowledge of page lifecycle, network idle, service workers, client-side rendering, and shadow DOM; experience debugging JavaScript and fluency with Chrome DevTools, CDP, HAR files, curl, and packet captures. - Comfort working independently when the path forward is not fully defined. Nice to have - Experience developing CDN, caching, or web performance systems. - Experience operating crawlers, headless browsers, or distributed content-acquisition systems at scale. - Contributions to a browser engine or JavaScript runtime.