Tools And Automation Engineer in United States

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We're seeking a Security Engineer to join our First-Party Hardware team. In this role, you will own the end-to-end security foundation for OpenAI's first-party AI hardware systems, working across hardware security, embedded security, system security, and practical deployment at data center scale. You will partner with silicon, hardware, firmware, infrastructure, manufacturing, operations, and security teams to define and deliver system-level device trust. This includes boot integrity, device identity, provisioning, attestation, management-plane security, storage encryption, debug controls, firmware update and recovery, RMA, and decommissioning. You will be accountable for turning threat models into requirements, requirements into implementation, and implementation into validation evidence that can support launch decisions. Location: San Francisco, CA (Hybrid: 3 days/week onsite) Relocation assistance available. In this role, you will: Own security requirements, threat models, validation strategy, and launch-readiness evidence for first-party hardware platforms from early design through production deployment. Design and review secure boot, measured boot, roots of trust, platform firmware resilience, firmware signing, recovery, and anti-rollback strategies across heterogeneous devices. Own device identity, provisioning, enrollment, attestation, certificate lifecycle, and key-management requirements across manufacturing and data center bring-up. Harden management

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role As a Supply Chain Program Manager, you will own material readiness and supply chain execution for critical hardware programs spanning custom silicon, systems, memory, storage, networking, and rack infrastructure. You will work cross-functionally with Engineering, Strategic Sourcing, Manufacturing Operations, Finance, Planning, Quality, and external suppliers to develop and execute scalable supply strategies that support aggressive product development and deployment timelines. This role requires deep understanding of hardware supply chains, material planning, NPI execution, supplier management, and operational scaling in constrained and rapidly evolving environments. In this role you will: Material Readiness & Supply Planning - Own end-to-end material readiness across NPI and production phases, including building the necessary framework and processes for enablement. Drive supply planning and execution for long lead-time and constrained commodities including ASICs, HBM, DDR, SSDs, networking, optics, power, thermal, and mechanicals. Build and manage material readiness plans aligned to proto/pre-EVT, EVT, DVT, PVT, and mass production schedules. Monitor supply health, lead times, inventory positions, allocation risk, and capacity constraints. Drive shortage management, allocation mitigation, and recovery planning. Coordinate supply commits, forecast alignment, and supply continuity planning with suppliers and manufacturing partners. Cross-Functional Program Ma

About the Team Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference. About the Role We are looking for an engineer who wants to take the world's largest and most capable AI models and optimize them for use in a high-volume, low-latency, and high-availability production and research environment. In this role, you will: Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production. Work alongside researchers to enable advanced research through awesome engineering. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack. Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues. Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware. You might thrive in this role if you: Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference. Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. Have at least 5 years of professional software engineering experience. Have or can quickly gain familiarity with PyTorch, NVidia GPUs and the software stacks that optimize them (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink, etc. Have experience architecting, building, observing, and debugging production distributed systems. Bonus point if worked on performance-critical distributed systems. Have need

About the Team Our Applied team brings OpenAI technologies to consumers and businesses around the world. We collaborate across research, engineering, design and business functions to turn cutting-edge AI advancements into impactful real-world applications. Our team has been behind notable product launches ( ChatGPT , API , Sora ), creating tools that help developers write code, enable businesses to operate more efficiently, and empower individuals to learn and create. As AI capabilities rapidly evolve, we focus on ensuring that our products are safe, accessible, and beneficial to all. About the Role As a Data Scientist on the Applied Product team, you will contribute to a data-driven product development culture for consumer and enterprise products at OpenAI. This is critical as our products reach millions of users and businesses worldwide. We are focused on aligning both research and product development to drive measurable impact for these individuals and organizations alike. You should expect to define our north-star metrics, design A/B tests, and establish source-of-truth dashboards that the entire company can use to answer their own product questions. Most importantly, you should expect to be a core member of the product development team. This role is based in San Francisco, CA or Seattle, WA. 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: Embed with the product development team as a trusted partner, uncovering new ways to improve the product and drive growth Define and interpret A/B tests that help answer critical questions about the impact of model and UX changes to our product Establish a data-driven product development culture by defining, tracking, and operationalizing feature-, product-, and company-level metrics Develop and socialize dashboards, reports, and other ways of enabling the team and company to answer product data questions in a self-serve way You might thrive

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are seeking a Technical Lead to lead deployment and operations for OpenAI’s Silicon & Systems team. This person will become the Directly-Responsible Individual responsible for bringing OpenAI’s custom silicon and associated systems into data center environments, ensuring successful deployment, bring-up, validation, operational readiness, and ongoing reliability at scale. This role sits at the intersection of silicon, systems, infrastructure, data center operations, and software. You will lead a team focused on taking new hardware platforms from lab validation into production data center deployment. You will be responsible for building the operational processes, technical workflows, tooling, and cross-functional alignment required to deploy and operate custom AI hardware reliably in OpenAI’s supercomputing infrastructure. The ideal candidate is both a strong leader and a deeply technical operator. You should be comfortable staying close to the technical details of hardware bring-up, fleet deployment, debugging, system validation, data center integration, and production operations. This role requires strong execution, excellent cross-functional judgment, and the ability to drive clarity in ambiguous, fast-moving environments. In this role, you will: Lead a team responsible for deployment and operations of OpenAI’s custom silicon and systems in data center environments Own the path from hardware bring-up and validation through production deployment, operati

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role On the Accelerators team, you will help OpenAI evaluate and bring up new compute platforms that can support large-scale AI training and inference. Your work will range from prototyping system software on new accelerators to enabling performance optimizations across our AI workloads. You’ll work across the stack, collaborating with both hardware and software aspects - working on kernels, sharding strategies, scaling across distributed systems, and performance modeling. You'll help adapt OpenAI's software stack to non-traditional hardware and drive efficiency improvements in core AI workloads. This is not a compiler-focused role, rather bridging ML algorithms with system performance - especially at scale. In this role, you will: Prototype and enable OpenAI's AI software stack on new, exploratory accelerator platforms. Optimize large-scale model performance (LLMs, recommender systems, distributed AI workloads) for diverse hardware environments. Develop kernels, sharding mechanisms, and system scaling strategies tailored to emerging accelerators. Collaborate on optimizations at the model code level (e.g. PyTorch) and below to enhance performance on non-traditional hardware. Perform system-level performance modeling, debug bottlenecks, and drive end-to-end optimization. Work with hardware teams and vendors to evaluate alternatives to existing platforms and adapt the software stack to their architectures. Contribute to runtime improvements, compute/communication over

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role As a software engineer on the Scaling team, you’ll help build and optimize the low-level stack that orchestrates computation and data movement across OpenAI’s supercomputing clusters. Your work will involve designing high-performance runtimes, building custom kernels, contributing to compiler infrastructure, and developing scalable simulation systems to validate and optimize distributed training workloads. You will work at the intersection of systems programming, ML infrastructure, and high-performance computing, helping to create both ergonomic developer APIs and highly efficient runtime systems. This means balancing ease of use and introspection with the need for stability and performance on our evolving hardware fleet. This role is based in San Francisco, CA, with a hybrid work model (3 days/week in-office). Relocation assistance is available. In this role, you will: Design and build APIs and runtime components to orchestrate computation and data movement across heterogeneous ML workloads. Contribute to compiler infrastructure, including the development of optimizations and compiler passes to support evolving hardware. Engineer and optimize compute and data kernels, ensuring correctness, high performance, and portability across simulation and production environments. Profile and optimize system bottlenecks, especially around I/O, memory hierarchy, and interconnects, at both local and distributed scales. Develop simulation infrastructure to validate runtime b

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role As a Hardware Chips Programs Manager at OpenAI, you will help bring our chips hardware roadmap to life, navigating an array of technical and partnership challenges. We’re looking for people excited to push the frontiers of computing by navigating technical explorations and are passionate about building. 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: Manage the design and implementation planning of our ML acceleration hardware, working across technical, cross-functional and external stakeholders Lead planning and scheduling of chip hardware designs with our strategic partners and vendors Coordinate and marshal internal resources and communication for efficient interaction with partners and vendors. You might thrive in this role if you: Have experience as a technical program manager for data center hardware products (server, GPU, TPU, networking, storage and so on) Know the whole end-to-end system program management from concept, design, production, deployment into the data center Have some experience with System SW programs through NPI Want to help design some of the world’s largest supercomputing systems, working at the edge of complex hardware challenges Enjoy working with and enabling world-class AI Researchers and Engineers Are passionate about the technical program function, and enjoy independently owning and delivering on your tea

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are seeking a Operations Program Manager (OPM) to serve as the single-threaded operational leader for new hardware introductions (NPI) and production ramps across OpenAI’s AI infrastructure systems. This role combines hands-on execution with strategic ownership. You will be responsible for defining the operating model, aligning cross-functional stakeholders, setting the critical path, making informed tradeoffs, escalating decisively, and ensuring hardware programs deliver on schedule, quality, cost, and scalability. Success in this role requires comfort operating in ambiguity, influencing without authority, and driving alignment across internal teams and external partners—while keeping eyes firmly on long-term system scalability and repeatability. In this role, you will: Strategic & Leadership Ownership Act as the single-threaded owner for operational readiness across NPI and ramp, accountable for outcomes from early bring-up through sustained production Translate OpenAI’s infrastructure strategy and engineering objectives into clear operating plans, execution priorities, and decision frameworks Drive alignment across Engineering, Operations, Strategic Sourcing, Finance, Capacity Planning, and Executive stakeholders by framing tradeoffs, risks, and recommendations Proactively identify inflection points where decisions or investments are required to protect long-term scale, reliability, or cost targets Influence operational strategy with manufacturing par

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for signal integrity (SI) system design engineers who have a deep expertise in the SI area, and hold strong system level design knowledge 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: Lead system signal integrity (SI) design for AI supercomputer product in the data center application. Collaborate with chip, package, boards, rack and system engineers, design partners to drive system SI design and develop innovative interconnect and high-speed technologies Identify and evaluate new technologies and methodologies to improve signal and power integrity in product design, and contribute to the development of new products and technology by providing expertise in signal integrity Perform simulation and modeling to identify and troubleshoot signal integrity issues Lead system interconnect design, bring up and qualification As the scope of the role and team grows, understand and influence roadmaps for hardware partners for our datacenter networks, racks, and buildings. You might thrive in this role if you: Have at least 10 years of industry experience, including experience design hardware system and SerDes testing for data center applications Have a strong bias toward action, and won’t take no for an answer. Have experience and good knowledge of system design experience in the SI areas, from chip, SerDes, board, rack level Have ex

About the team OpenAI’s Education team is building products and experiences that help learners, educators, and institutions benefit from AI in ways that are rigorous, useful, and grounded in real learning outcomes. The work spans both consumer and B2B education, with close collaboration across engineering, learning science, design, data, and research. This team sits in a highly strategic investment area for OpenAI, with strong opportunities to shape how product ideas flow across consumer and institution-facing experiences. Some of our recent work: New Education Plugins for ChatGPT Work and Codex New tools for understanding AI and learning outcomes Education for countries Advancements in higher education Early product work - Introducing Study Mode About the role We’re looking for a product-minded Full Stack Engineer to help build OpenAI’s education products from the ground up. You’ll own end-to-end development across the stack, from early concepting and prototyping through production launch and iteration. This is an opportunity to work on a highly strategic, early-stage product area where engineering judgment, product sense, and customer empathy all matter. You’ll partner closely with leaders across the education org, including learning scientists, researchers, designers, and cross-functional partners, to turn emerging ideas into durable product experiences for schools, universities, and other education stakeholders. In this role, you will: Build and ship product experiences across the full stack for OpenAI’s education offerings Own projects end-to-end, from ideation and technical design through implementation, launch, and iteration Work closely with learning scientists and researchers to translate learning goals and evidence into product decisions Collaborate with design, data, and cross-functional partners to build thoughtful, high-quality user experiences Help define the engineering foundation for a growing education pod, including patterns, systems, and technical

About the team: OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the role: We are seeking an experienced Optical Network Engineer to lead Laser related work within our optical interconnect efforts for large-scale compute systems. The role also requires broad, hands-on optical validation experience across IM/DD-based interconnects, working from lab characterization through production readiness and scaled deployment. In this role you will: Drive laser-focused requirements and technical direction within the broader optical interconnect roadmap. Lead evaluation and validation of optical components and subsystems, including laser-based elements, in lab and production-representative environments. Support end-to-end optical testing for IM/DD interconnects (e.g., module/system bring-up, characterization, debug, and readiness for scale). Work with external partners to align on development milestones, performance targets, and quality expectations. Own technical issue triage and resolution across performance, reliability, and manufacturability topics. Collaborate across internal teams to support integration, rollout, and operational success at scale. You might thrive in this role if you have: Strong experience in laser-focused optical engineering (development, validation, manufacturing readiness, or field support). Broad hands-on background with IM/DD optical technologies and optical test/debug workflows. Experience working with external suppliers/manufacturing partners and production-oriented execution. Demonstrated ability to debug complex t

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are seeking an experienced SoC Architect to lead the definition and development of next-generation custom AI silicon for edge deployments. This role will be responsible for shaping the architecture of highly efficient, high-performance SoCs optimized for machine learning inference and on-device intelligence. You will work cross-functionally with internal engineering teams and external ecosystem partners to translate product requirements into scalable silicon solutions, driving execution from concept through delivery. In this role you will: Define the architecture and technical roadmap for custom SoCs targeted for edge applications. Drive system-level tradeoff analysis across compute, memory, interconnect, power, thermal, and cost constraints. Architect energy-efficient ML compute subsystems optimized for inference workloads and real-world deployment environments. Collaborate with internal hardware, software, systems, and product teams to align architecture with platform needs. Partner with external silicon vendors, IP providers, and manufacturing partners to execute development plans. Lead hardware/software co-design efforts to maximize performance per watt and end-to-end system efficiency. Guide implementation teams through microarchitecture, RTL development, validation, and bring-up phases. Operate effectively in agile development environments and help teams deliver against aggressive schedules and milestones. You might thrive in this role if: Proven exper

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. At Snowflake, we are shaping how data becomes the center piece of the agentic enterprise. Time to value is what’s most critical to our customers. For them, moving from other platforms to Snowflake is key to unlocking new business opportunities and out-innovating their competition. With AIM Virtualization we’re redefining interoperability for the modern data stack. Our platform makes existing applications instantly work on Snowflake by bringing the core tenets of virtualization to the database. With our runtime, customers move to Snowflake without changing SQL or APIs. As a result, AIM Virtualization makes time-consuming migrations obsolete. Our platform is uniquely situated at the intersection of database internals and their practical application. Our team gets to tackle some of the most intricate database implementation challenges. All while pioneering an industry-first framework which customers consistently describe as “too good to be true”. If you’re looking to work on interesting problems that truly matter to our customers while advancing how we can use AI across the organization, this is the team for you. We are looking for AI-first engineers who are not afraid to take on hard and unusual challenges. We are one of Snowflake’s leading teams in AI-driven software synthes

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About Dynamic Tables Dynamic Tables (DTs) are Snowflake's declarative streaming transformation primitive. Customers define a SQL query and a freshness target; Snowflake handles the rest: orchestrating refreshes, maintaining snapshot consistency across a DAG of dependencies, and automatically incrementalizing the computation so that cost scales with what changed. Dynamic Tables is one of the fastest growing products at Snowflake and is a core part of Snowflake’s Data Engineering strategy. The Dynamic Tables performance team is responsible for making incremental refresh fast, predictable, and cost-efficient across increasingly complex query shapes. As a Staff Engineer on this team, you will own the technical direction for critical performance initiatives and be a force multiplier for the engineers around you. What You'll Do Lead the design and implementation of performance improvements to the incremental view maintenance engine, including multi-join incrementalization, novel incrementalization semantics, incremental window functions, and stacked operations. Help define the roadmap for the incremental view maintenance engine, identifying key performance, scalability, and correctness milestones, prioritizing high-impact enhancements, and aligning technical investments with prod