About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity! 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. Key Responsibilities Co-design future hardware for programmability and performance with our hardware vendors Assist hardware vendors in developing optimal kernels and add support for it in our compiler Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory h
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About the Team The Human Data team at OpenAI is responsible for identifying and mitigating risks in advanced AI systems by designing evaluations, surfacing vulnerabilities, and collaborating closely with researchers to strengthen model reliability and public trust. About the Role As a Research Program Manager, you will lead initiatives that test the safety and robustness of OpenAI’s models through creative experimentation and structured evaluation. You’ll coordinate efforts across research and engineering teams to transform ambiguous risks into concrete research programs and influence future model development and deployment. We’re looking for people who are technically savvy, comfortable with ambiguity, and excited about shaping the future of safe AI. 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 programs that explore unexpected model behaviors and identify failure modes. Translate vague or emergent risk signals into clear priorities and actionable research plans. Design and run creative evaluations, experiments, and red-teaming campaigns. Collaborate with research, product, and deployment teams to integrate findings into model training and deployment cycles. Develop repeatable systems for tracking model performance and understanding emerging behavior patterns. You might thrive in this role if you: Have strong experience in technical program management, with excellent organizational and communication skills. Are familiar with large language models, prompt engineering, or model evaluation techniques. Are comfortable managing fast-paced, high-uncertainty projects and shaping them from the ground up. Are creative and resourceful in devising new methods for testing model behavior and performance. Can effectively coordinate across technical and non-technical stakeholders to drive alignment and execution. About OpenAI OpenAI is an AI resear
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. Role summary We are seeking a Networking Operating System Firmware Engineer to help bootstrap and scale the switching layer of our AI supercomputers. In this role, you will build and maintain custom NOS images from scratch, using open source components from SONiC, SAI, FRR, and related networking stacks while working across the Linux kernel, switch ASIC SAI/SDKs, platform drivers, control-plane services, and orchestration layers. This is a software engineering role that requires a deep understanding of networking, NOS internals, switch hardware, and production systems. You will design, implement, test, and debug production NOS software across platform drivers, routing and control-plane state, ASIC programming, observability, and fleet integration. The engineer in this role should be able to work through ambiguous, open-ended technical problems and drive feature development across software, hardware, and vendor boundaries. 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 Design, develop, and maintain custom NOS images for large-scale AI fabrics, using open source components from SONiC, FRR, and related networking stacks. Integrate, build and configure Linux kernel components, device drivers, switch ASIC SDKs, and SAI layers. Bring up new switch platforms, including thermal and fan control, power monitoring, transceiver management, watchdogs, OSFP CMIS, L
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 looking for an embedded engineer to help build firmware and associated modeling software for OpenAI’s in house AI accelerator. This role involves designing and developing drivers and functional models for a large array of HW components, writing high throughput and low latency firmware code, investigating bring-up and production issues. Responsibilities Design and implement drivers for hardware peripherals, including those related to AI chips. Design and implement functional software models to simulate SoC uncore logic and enable FW testing against the model Design and implement low-latency and high throughput embedded SW to manage HW resources. Work with adjacent software and hardware teams to implement requirements, debug issues and shape future generations of the hardware. Collaborate with vendors to integrate their technologies within our systems. Bring up and debug firmware/driver on new platforms. Come up with processes and debug issues raised in the field. Set up monitoring, integration testing and diagnostics tools. Qualifications 5+ years of experience working in embedded SW space. Ability to thrive in ambiguity and learn new technologies. Strong programming skills in C/C++ and/or Rust. Experience developing high throughput, low latency and multi-threaded code. Experience working with real time operating systems (RTOS). Experience developing hardware drivers and working with hardware Experience with HW/SW co-design Knowledge of common embedded pr
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 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 OpenAI is developing custom silicon to power the next generation of frontier AI models. We’re looking for experienced Design Verification (DV) Engineers to ensure functional correctness and robust design for our cutting-edge ML accelerators. You will play a key role in verifying complex hardware systems—ranging from individual IP blocks to subsystems and full SoC—working closely with architecture, RTL, software, and systems teams to deliver reliable silicon at scale. In this role you will: Own the verification of one or more of: custom IP blocks, subsystems (compute, interconnect, memory, etc.), or full-chip SoC-level functionality. Define verification plans based on architecture and microarchitecture specs. Develop constrained-random, directed, and system-level testbenches using SystemVerilog/UVM or equivalent methodologies. Build and maintain stimulus generators, checkers, monitors, and scoreboards to ensure high coverage and correctness. Drive bug triage, root cause analysis, and work closely with design teams on resolution. Contribute to regression infrastructure, coverage analysis, and closure for both block- and top-level environments. You might thrive in this role if you have: BS/MS in EE/CE/CS or equivalent with 3+ years of experience in hardware verification. Proven success verifying complex IP or SoC designs in industry-standard flows Proficient in SystemVerilog, UVM, and common simulation and debug tools (e.g., VCS, Questa, Verdi). Strong knowledge
About the Team OpenAI’s Hardware organization develops system and infrastructure solutions tailored to the demands of advanced AI workloads. We work across the full stack—from silicon to system integration—partnering closely with internal teams and external vendors to define and deliver next-generation AI infrastructure. Our team focuses on defining scalable, high-performance system architectures and reference designs that balance performance, cost, and operational efficiency across rapidly evolving technologies. About the Role We are seeking a 3P Architect to define and drive rack- and cluster-level reference designs in collaboration with external partners. This role is responsible for translating workload requirements and system-level goals into concrete architectures, aligning partners on critical design attributes, and ensuring vendor roadmaps meet our infrastructure needs. You will work closely with performance modeling and internal architecture teams to evaluate tradeoffs, while owning the end-to-end definition and execution of third-party system designs. This includes identifying gaps in current technologies, driving vendor development, and shaping future infrastructure capabilities. This role requires strong system intuition, cross-functional leadership, and the ability to operate effectively across internal teams and external ecosystems. 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. Key Responsibilities Define rack- and cluster-level reference architectures for AI infrastructure deployments. Translate workload requirements into clear system design specifications and partner deliverables. Collaborate with performance modeling teams to evaluate architectural tradeoffs and system behaviors. Align internal stakeholders and external partners on critical system attributes (performance, cost, power, reliability, scalability). Identify gaps in current technology offerings and dr
About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and support next-generation infrastructure design. About the Role We are seeking an Performance Modeling Engineer to support the development and application of modeling tools used to evaluate AI system performance and inform architectural decisions. In this role, you will partner closely with Senior Performance Modeling Engineers and the Performance Modeling Lead to analyze system behavior, run simulations and analytical models, and help evaluate tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks while developing a strong foundation in system architecture and AI infrastructure. This role is ideal for early-career engineers with 1–2 years of experience in software engineering, systems analysis, or performance modeling who are excited to grow in large-scale infrastructure and hardware/software systems. 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. Key Responsibilities Support the development and maintenance of performance modeling tools and frameworks Assist in building models to evaluate system behavior across compute, memory, networking, and interconnect subsystems Help analyze distributed system scaling behavior and identify performance bottlenecks Run simulations and analytical models to support architecture and infrastructure decisions Partner with senior engineers to evaluate design tradeoffs across hardware and system components Interpret modeling outputs and help translate findings into clear recommendations Vali
About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and inform next-generation infrastructure design. About the Role We are seeking Performance Modeling Engineers to develop and apply modeling tools that evaluate AI system performance and inform architectural decisions. In this role, you will work closely with the Performance Modeling Lead and partner teams to analyze system behavior, run simulations or analytical models, and help quantify tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks and applying them to real-world questions that impact system design and vendor decisions. This role is well-suited for engineers with strong software or modeling backgrounds who are interested in developing deeper expertise in system architecture and AI infrastructure. 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. Key Responsibilities Develop and maintain performance modeling tools and frameworks. Build models to evaluate system behavior across: compute, memory, and interconnect subsystems distributed system scaling and bottlenecks. Run simulations and analytical models to support architectural tradeoff analysis. Collaborate with performance modeling lead and system architects to answer forward-looking design questions. Analyze and interpret modeling outputs, translating results into actionable insights. Validate models against real system measurements and workload behavior. Contribute to improving modeling fidelity, usability, and scalability. Qualifications Strong software engineeri
About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with research, software, and external hardware partners to shape the next generation of AI systems, from silicon through full-scale deployments. Our team focuses on understanding and optimizing performance across the full system stack—ensuring that architectural decisions are grounded in rigorous, quantitative analysis of real-world workloads. About the Role We are seeking a Performance Modeling Lead to build and lead a small, high-impact team responsible for answering forward-looking architectural questions across AI infrastructure systems. You will develop modeling frameworks and methodologies to evaluate system-level tradeoffs and guide key design decisions. Your work will directly influence reference architectures, vendor designs, and long-term infrastructure strategy. This role sits at the intersection of AI workloads, system architecture, and quantitative modeling, and requires strong technical judgment, ownership, and the ability to translate complex analysis into clear, actionable guidance. 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. Key Responsibilities Build and own a performance modeling framework/toolchain to evaluate AI systems across multiple levels of abstraction. Analyze and quantify architectural tradeoffs across compute, memory, networking, storage, and system topology. Develop performance models to guide decisions on: scale-up vs. scale-out architectures interconnect and network design memory hierarchy and system balance. Translate modeling outputs into clear recommendations for internal teams and external hardware vendors. Influence reference designs and vendor roadmaps through data-driven insights. Partner closely with machine learning, systems, and hardware teams to understand workload characte
About the Team OpenAI’s Stargate and 3P Engineering teams are responsible for building and scaling the external infrastructure ecosystem that powers advanced AI systems. We work across hyperscalers, colocation providers, cloud partners, and strategic third-party operators to turn contracted capacity into production-ready compute. Our scope spans the full lifecycle of external deployments: commercial alignment, technical readiness, network integration, hardware enablement, operational readiness, and long-range scaling strategy. As OpenAI’s infrastructure footprint expands globally, we need leaders who can convert complex partner environments into reliable, high-velocity capacity for training and inference workloads. About the Role We are seeking a Technical Program Manager, Token-as-a-Service (TaaS) to lead delivery of external compute capacity that directly serves OpenAI model workloads. In this role, you will own complex cross-functional programs that transform third-party infrastructure into usable tokens at scale. You will partner across engineering, capacity planning, networking, hardware, finance, product, and external providers to ensure that deployed capacity translates into real production throughput. This role sits at the intersection of infrastructure execution, systems readiness, and business impact. Success requires strong technical fluency, elite program management, and the ability to drive accountability across internal teams and external partners. This is a high-visibility role with direct impact on OpenAI’s ability to scale model training and inference globally. This role is based in San Francisco, CA, with a hybrid work model of 3 days in office per week. Relocation assistance is available. Key Responsibilities Lead end-to-end delivery programs that convert external infrastructure capacity into production-ready token supply. Own readiness across compute, storage, networking, security, and operational dependencies for third-party environments. Build
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
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 looking for a systems-minded engineer to help advance our kernel development, performance engineering, and hardware-software co-design capabilities, with a particular focus on AI-assisted workflows and tooling. This person will work at the intersection of kernel optimization, developer tooling, observability, and research infrastructure, helping us improve both how production kernels are built and optimized, and how future hardware-software systems are designed and evaluated. The role is ideal for someone who is excited by low-level performance work, but also sees AI and automation as powerful tools for accelerating engineering velocity. You will help define the future of kernel engineering in the era of AI-assisted development. In this role, you may: Build developer tooling and workflows that make kernel development and performance optimization faster, more scalable, and easier to debug, integrate, and deploy. Develop observability, diagnostics, and validation infrastructure that makes AI-assisted optimization systems more interpretable, reliable, and effective. Optimize production kernels end to end by formulating optimization problems, running search loops, analyzing bottlenecks, debugging generated implementations, and landing improvements into production. Design abstractions, interfaces, and automation systems that accelerate kernel optimization, correctness validation, and hardware-software co-design. Improve AI-assisted optimization systems for sp
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Why Patients Need You Pfizer’s purpose is to deliver breakthroughs that change patients’ lives. Research and Development is at the heart of fulfilling Pfizer’s purpose as we work to translate advanced science and technologies into the therapies and vaccines that matter most. Whether you are in the discovery sciences, ensuring drug safety and efficacy or supporting clinical trials, you will apply cutting edge design and process development capabilities to accelerate and bring the best-in-class medicines to patients around the world. What You Will Achieve As a Senior Associate Scientist, you will be at the center of our operations and you’ll find that everything we do, every day, is in line with an unwavering commitment to quality. You will be part of a team to support the preclinical evaluation and early clinical development of mRNA and protein based viral vaccines. You will be responsible for performing and developing immunoassays supporting various viral programs to monitor the immune responses elicited by vaccine candidates. You will be using your scientific knowledge to adapt and develop standard methods and techniques by applying prior work experience and consulting others. You should possess a strong work ethic and collaborative spirit and be adaptable to fast-paced environments. It is your innovative scientific temperament that will help in making Pfizer ready to achieve new milestones and help patients across the globe. How You Will Achieve It Perform assays to analyze immune responses to vaccine candidates that include (but are not limited to) cell culture, neutralization assays, other functional antibody assays, Luminex, and ELISAs in BSL-2 environments. Generate, characterize and tract critical reagents for preclinical bio-functional studies to support vaccine development. Assist with preclinical bio-functional assay development and t
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