Ai Infrastructure Systems Engineer Jobs

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: Multi-Agent systems are becoming an increasingly important part of how AI is deployed, whether via fast small-model subagents inside a product, or large groups of agents solving very large problems . Training Claude to be maximally effective and safe within large groups is a challenging new area of reinforcement learning, and represents a new axis for scaling test time compute. We are looking for researchers who have experience training multi-agent systems at the largest scale and an appreciation for the incentives and mechanism design that come into play. Responsibilities: Help create and optimize environments and data for model training that maximize Claude’s performance or ease of use on agentic tasks Ideate, develop, and compare the performance of different agent harness configurations (eg memory, context management, communication architectures for agents) Design and implement rigorous quantitative benchmarks for large scale agentic tasks Work with our product org to find solutions to our most vexing challenges in applying agents to our products You may be a good fit if you: Have experience with large-scale RL on language models Have experience training multi-agent systems Enjoy going deeply into the roots of a problem and understanding its foundations, rather than its surface. Have good communication skills and an interest in working with other researchers on difficult tasks Have a passion for making powerful technology safe and societally beneficial Are excited for a mission-driven org with fast-paced, impactful work Representative projects: Design and build reinforcement learning environments to train groups of

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: Running machine learning (ML) algorithms at our scale often requires solving novel systems problems. As a Performance Engineer, you'll be responsible for identifying these problems, and then developing systems that optimize the throughput and robustness of our largest distributed systems. Strong candidates here will have a track record of solving large-scale systems problems and will be excited to grow to become an expert in ML also. You may be a good fit if you: Have significant software engineering or machine learning experience, particularly at supercomputing scale Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Want to learn more about machine learning research Care about the societal impacts of your work Strong candidates may also have experience with: High performance, large-scale ML systems GPU/Accelerator programming ML framework internals OS internals Language modeling with transformers Representative projects: Implement low-latency high-throughput sampling for large language models Implement GPU kernels to adapt our models to low-precision inference Write a custom load-balancing algorithm to optimize serving efficiency Build quantitative models of system performance Design and implement a fault-tolerant distributed system running with a complex network topology Debug kernel-level network latency spikes in a containerized environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. Fo

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are seeking a GCC Compiler Engineer to design, develop, and optimize compilers for next-generation RISC-V and AI compute architectures. You will work across hardware and software teams to improve performance, programmability, and integration of our custom toolchains into real applications. This role is fully hands-on and central to how developers interact with Tenstorrent hardware across both traditional compute and advanced machine learning workloads. This role is Hybrid, based out of Santa Clara, CA, Austin, TX, or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced compiler engineer with deep knowledge of GCC and LLVM internals, comfortable optimizing for custom hardware targets. Strong C/C++ developer with a solid grasp of algorithms, data structures, and performance analysis. Collaborative and analytical, able to work across hardware and software domains to deliver efficient, high-performance toolchains. Passionate about enabling breakthrough compute architectures through compiler innovation and software-hardware co-design. What We Need Design, develop, and optimize GCC and/or LLVM compilers for Tenstorrent’s cust

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us—that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale—from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Simulation is at the core of autonomy development. The Simulation team is responsible for building the simulator that powers all simulations at Nuro, allowing us to develop and test our autonomous driving technology with confidence. The team focuses on solving many novel simulation problems with innovative and creative solutions - from synthesizing sensor data and automated scenario generation, to performance and resource optimization, to framework and interface design - collaborating with teams across the company to set and expand the range of what’s possible to simulate. About the Work Expand the functionality, performance, and usability of our simulator. Develop innovative solutions to improve simulation realism and coverage through synthesis. Design and build solutions to unify and simplify the interactions of complex systems. Work across a large array of potential efforts, ranging from new greenfield projects to expandi

About the Team Dots is building personal AI agents that help people make progress on their goals, including when they are away from ChatGPT. These agents can learn preferences, maintain context, work across applications, and use cloud computers to carry out tasks. Our team brings together product engineering, design, and research to turn frontier model capabilities into useful everyday experiences. We are defining how people delegate work, understand what an agent is doing, and stay in control. Engineers help shape both the product and the systems behind it, from early prototypes through launch and iteration. About the Role We are looking for Senior and Staff Full Stack Software Engineers to build Dots product experiences from the interface through the services that power them. You will help define how people delegate tasks to personal agents, follow their progress, and collaborate with them over time. This role combines hands-on product development with the systems work needed to make persistent, asynchronous agent experiences reliable. In this role, you will: Build and launch features across web interfaces, APIs, backend services, and data models. Create workflows for task creation, progress updates, agent feedback, and results that remain coherent across sessions and devices. Translate emerging model capabilities into product prototypes with research, product, and design partners. Design clear interfaces between product surfaces and agent execution systems. Improve performance and reliability across the stack, including user-facing latency and recovery from partial failures. Own projects from early exploration through architecture, implementation, launch, and iteration based on user feedback. Help establish technical direction, testing practices, and observability as the product grows. You might thrive in this role if you: Have significant experience building and shipping products across frontend and backend systems. Can move comfortably between user interfaces,

About the Team Dots is building personal AI agents that help people make progress on their goals, including when they are away from ChatGPT. These agents can learn preferences, maintain context, work across applications, and use cloud computers to carry out tasks. Our team brings together product engineering, design, and research to turn frontier model capabilities into useful everyday experiences. We are defining how people delegate work, understand what an agent is doing, and stay in control. Engineers help shape both the product and the systems behind it, from early prototypes through launch and iteration. About the Role We are looking for Senior and Staff Software Engineers to build the mobile web experience for Dots. You will create responsive, accessible interfaces that let people start work, follow progress, and guide their agents from a phone or browser. You will help establish interaction patterns for ongoing, asynchronous work and make sophisticated agent capabilities feel clear and approachable. In this role, you will: Design and ship mobile web experiences for creating tasks, reviewing agent activity, and providing feedback or direction. Build interfaces that handle streaming updates, long-running tasks, interrupted sessions, and changing connectivity. Improve responsiveness, loading performance, accessibility, and usability across screen sizes and browsers. Partner with design and product to prototype interaction patterns that give users visibility and control over agent actions. Work with backend and full stack engineers on APIs, client state, and reliable synchronization between the interface and agent services. Own features from exploration and technical design through launch, measurement, and refinement. Help set frontend architecture and engineering practices while staying hands-on with implementation. You might thrive in this role if you: Have substantial experience shipping polished web applications, with deep expertise in mobile web development

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a member of the GTM team at Anthropic, you will be a Staff Forward Deployed Engineer (FDE) who embeds directly with our most strategic customers and leads the technical direction of their AI adoption. Customers bring you in to lead, not only to implement: you decide what should be built, and then make sure it gets built well. You will work with customer teams to ship advanced AI applications that solve real world business problems, and guide the architecture and advisory work that surrounds those builds across an account. Working closely with our Research, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability. You will sit at the frontier of enterprise AI deployments and help shape our forward-deployed motion as it scales. We expect Staff FDEs to set direction under ambiguity and represent Anthropic at the highest level in customer environments. In this role, you guide architecture and build initiatives across workstreams, working directly with senior technical and business stakeholders and owning outcomes that span an account's roadmap. You don't need to have shipped agents to production. You do need deep experience building and operating production systems, hands-on time with agents, and the judgment to lead architecture and advisory work with enterprise customers. Responsibilities Own technical strategy for a key account or vertical, in partnership with accou

About the Team The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments as well as other OpenAI products worldwide. We operate across the full funnel - from awareness and acquisition through activation, retention, and expansion - using a combination of global performance marketing, AI-powered workflows, in-product optimization, insights, experimentation, and creative ops engineering. Our Growth Marketing team is a rapidly scaling functional area, accelerating growth by connecting out-of-product and in-product experiences into seamless journeys that acquire, retain, and re-engage users, unlocking ChatGPT’s transformative potential in users’ daily lives. We work cross-functionally with product, engineering, design, data science, finance, and marketing to unlock scalable growth levers and deliver measurable impact across diverse markets. This team thrives on rapid testing, rigorous measurement, and creative problem solving, all while keeping user value at the center of our decision-making. About the Role In this role, you will build and run the creative and advertising operations system that powers OpenAI’s paid marketing programs. You will connect Creative and Growth Marketing teams, establish clear processes for producing and launching high-quality ads, and keep the operational details behind paid campaigns organized, accurate, and scalable. You will help translate growth priorities into creative briefs and testing roadmaps, coordinate assets and approvals across internal teams and external partners, and turn performance results into clear next steps. This role is based in San Francisco, CA. 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: Build and manage the end-to-end paid creative operating system , including creative intake, briefing, production, asset delivery, approvals, trafficking, launch, reporting, and iteration. Serve as the day-to-da

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 bi

About the team The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments and other OpenAI products worldwide. We work across the full funnel—from awareness and acquisition through activation, retention, and expansion—using experimentation, data science, machine learning, and product engineering to help more people discover and realize durable value from OpenAI’s products. Our team partners closely with Product, Engineering, Data Science, Design, Finance, Lifecycle, and Growth Marketing. We move quickly, test rigorously, and hold a high bar for measurement, privacy, reliability, and user trust. About this role: We are looking for a Machine Learning Engineer to build the models and decision systems that optimize paid marketing investment for ChatGPT and other OpenAI products. You will develop budget allocation and control algorithms that determine where to invest, how quickly to spend, and how to adjust as performance changes. The challenge is to make reliable decisions from noisy, delayed, and incomplete signals. You will combine machine learning, optimization, and experimentation to improve incremental growth and long-term user value within budget and efficiency constraints. You will own this work from problem formulation and prototyping through deployment, evaluation, and ongoing operation. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to eligible employees. In this role, you will: Build budget allocation algorithms. Decide how to distribute investment across channels, campaigns, and markets using estimates of marginal returns, while accounting for diminishing returns, uncertainty, and business constraints. Develop spend pacing and adaptive control systems. Adjust budgets and spending rates as performance changes, balancing responsiveness with stability when feedback is delayed or noisy. Build in spend limits, monitoring, and safe fallback

Location: Bristol, London or Cambridge, UK About the job Help scale state-of-the art AI models across thousands of accelerators. As a Senior Machine Learning Engineer in the Applied AI team, you will contribute to advancing AI technology by developing and optimising new and existing AI models for our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Having visibility of the entire pipeline from novel accelerator hardware to state-of-the-art AI applications, and the software stack in-between, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. Furthermore, you’ll work closely with researchers in a rapidly-evolving field, where even the most senior engineers are constantly learning and adapting to exciting new challenges. We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale. We currently have multiple opportunities available in the team at Senior, Staff and Principal level and offer flexibility through a hybrid working model, from any of our UK offices. If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! The team and culture The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software, as well as our own hardware and software stack, to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. Our work spans from low-level kernel development and optimisation for novel hardware through to implementing and scaling research-level algorithms for the latest AI models. We collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and di

Location: Bristol, London or Cambridge, UK About the job Help scale state-of-the art AI models across thousands of accelerators. As a Senior Machine Learning Engineer in the Applied AI team, you will contribute to advancing AI technology by developing and optimising new and existing AI models for our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Having visibility of the entire pipeline from novel accelerator hardware to state-of-the-art AI applications, and the software stack in-between, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. Furthermore, you’ll work closely with researchers in a rapidly-evolving field, where even the most senior engineers are constantly learning and adapting to exciting new challenges. We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale. We currently have multiple opportunities available in the team at Senior, Staff and Principal level and offer flexibility through a hybrid working model, from any of our UK offices. If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! The team and culture The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software, as well as our own hardware and software stack, to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. Our work spans from low-level kernel development and optimisation for novel hardware through to implementing and scaling research-level algorithms for the latest AI models. We collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and di

Location: Bristol, London or Cambridge, UK About the job Help scale state-of-the art AI models across thousands of accelerators. As a Senior Machine Learning Engineer in the Applied AI team, you will contribute to advancing AI technology by developing and optimising new and existing AI models for our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Having visibility of the entire pipeline from novel accelerator hardware to state-of-the-art AI applications, and the software stack in-between, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. Furthermore, you’ll work closely with researchers in a rapidly-evolving field, where even the most senior engineers are constantly learning and adapting to exciting new challenges. We seek engineers with strong technical foundations who are curious and eager to understand and advance AI model implementation, at scale. We currently have multiple opportunities available in the team at Senior, Staff and Principal level and offer flexibility through a hybrid working model, from any of our UK offices. If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you! The team and culture The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software, as well as our own hardware and software stack, to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. Our work spans from low-level kernel development and optimisation for novel hardware through to implementing and scaling research-level algorithms for the latest AI models. We collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and di

About the Team The ChatGPT Space team is building a shared workspace where people and AI agents turn ideas into polished, editable work. Space brings teammates, ChatGPT, and dots together around shared knowledge and projects, with creation experiences spanning Pages, Sheets, Slides, and new kinds of artifacts. We want work to keep improving beyond the first draft, using shared context and collaboration to stay current as projects evolve. We work across product, design, and research, partnering closely with model training teams to shape how frontier models create and edit artifacts. We ship quickly, learn from real usage, and hold a high bar for craft, correctness, and speed. About the Role We’re hiring a Frontend Software Engineer to build a top-tier collaboration experience and help shape how people work with AI. This is a craft-heavy role: you’ll partner closely with design to prototype, iterate, and polish new interaction models, then turn them into reliable, high-performance product experiences. You’ll help define what great looks like for collaboration between people and agents: how shared context is represented, how contributions and changes are made understandable, and how users stay oriented and in control as work moves between teammates and AI. What You’ll Do Build and ship polished, high-performance UI for Space and its collaborative workflows. Partner tightly with design to turn prototypes into production-quality experiences, from layout and typography to motion and interaction details. Develop intuitive interfaces for creating and editing shared content, organizing project context, and reviewing contributions from teammates and AI as work evolves. Own frontend architecture decisions across component systems, state management, navigation, and rendering performance. Improve quality and reliability through testing, instrumentation, accessibility, and thoughtful UX for loading, errors, and concurrent changes. Collaborate with research, platform, and backend

About the team The Monetization team is a new cross-functional group spanning engineering, product, research, and design. We are building the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to create user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen trust, expand economic opportunity, and support OpenAI’s long-term innovation. We believe monetization should deliver clear user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem for developers and businesses. The team operates in a greenfield environment, moving quickly through prototyping, experimentation, and iterative deployment. We partner closely across Product, Design, and Research to bring new capabilities into real-world systems at global scale. About the role We’re looking for an experienced Software Engineer to lead the design and development of the systems that turn advertiser feeds (eg. retail feeds, travel feeds etc.) into relevant, reliably delivered ads. In this foundational role, you will build across the full ads lifecycle—from ingesting and organizing retailer or travel catalogs into efficient retrieval systems, supporting ranking models, and serving ads at scale. This role is well suited to an engineer with direct experience in product ads retrieval, ranking, and delivery, along with a strong understanding of merchant feeds and shopping systems such as Google Shopping, YouTube product ads, or Amazon. We also welcome engineers with Senior Staff-level or greater scope who have deep ownership of large-scale catalogs, search and indexing, ads serving, or closely related distributed systems. You will independently own complex systems, make sound technical tradeoffs, and help define the architecture and roadmap for Shopping/Travel/Feed Ads. You will collaborate closely with Ads ML, Ads Delivery, Product, Design, and Research to connect accurate, fresh advertiser