Responsable Production in United States

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A

About the team The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. As an AI Deployment Engineer (ADE) in the OpenAI for Government team, you’ll help government agencies transform their organization through solutions such as automated content generation, contextual search, and novel applications that make use of our newest, most exciting models and technology. About the Role We are looking for a driven solutions leader with a product mindset to partner with our public sector customers and ensure they achieve tangible value with GenAI. You will pair with government agencies (federal, state, and local), policymakers, and other public institutions to establish a GenAI strategy and identify the highest value applications. You’ll then partner with their technical teams, subject matter experts, systems integrators, and implementation partners to move from prototype through production. You’ll take a holistic view of their needs and design an architecture using the OpenAI API and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Global Affairs, Applied Research, and Product teams. This role is based in Washington, DC. We offer relocation support to new employees. In this role, you will: Deeply embed with our most sophisticated public sector customers as the technical lead, serving as their technical thought partner to ideate and build novel applications on our API and other OpenAI products. Work with senior customer stakeholders to identify the best applications of AI in their industry and to build/qualify a comprehensive backlog to support their AI roadmap. Intervene directly to accelerate customer time to value through building hands-on pr

About the Team The Scaling team is responsible for the architectural and engineering backbone of OpenAI’s infrastructure. We design and deliver advanced systems that support the deployment and operation of cutting-edge AI models. Our work spans system software, networking, platform architecture, fleet-level monitoring, and performance optimization. About the Role We’re hiring an SW Engineer to enable production workloads and end-to-end testing on new platforms. This role will include creating new test harnesses and platform stress benchmarks, porting existing inference and training workloads to new, sometimes early-access, systems/hardware, analyzing performance and bottlenecks, and characterizing the end-to-end behavior of new systems (compute, comms, storage, control plane, and failure modes). Key Responsibilities Port and validate key inference and training workloads on new platforms/SKUs as they arrive; drive correctness, performance, and stability to an internal readiness bar. Build a suite of benchmarks and stress tests that capture real E2E behavior of our workloads by exercising all aspects of a system, including CPU, GPU, memory subsystem, frontend, scale-up, and scale-out networking (including WAN traffic, NVlink and RDMA collectives), storage, thermals, and any other relevant parts. Deep-dive performance on distributed training/inference: Collective performance and tuning (across NCCL/RCCL and internal libraries) Overlap of compute/communication, kernel-level bottlenecks, memory bandwidth and scheduling effects Create repeatable test harnesses that run in CI / lab environments and produce actionable outputs (pass/fail, performance score, regression detection). Partner with systems + fleet bring-up engineers to ensure the platform is not only stable and performant, but also operationally usable and scalable (containerization, K8s integration, telemetry hooks, failure triage loops). Work cross-functionally with vendors and internal stakeholders by producing

About the Team The Stargate team is responsible for building the physical infrastructure that powers large-scale AI systems. We design and deliver next-generation data centers optimized for dense compute clusters, advanced networking, and rapidly evolving hardware platforms. This work sits at the intersection of hardware engineering, systems architecture, and infrastructure execution—translating cutting-edge compute roadmaps into scalable, production-ready environments. Our teams partner across silicon vendors, server and storage OEMs, networking teams, and data center engineering organizations to bring new capacity online quickly, reliably, and at global scale. About the Role We are seeking a CPU & Storage Technical Lead to define and drive the server compute and storage architecture strategy for Stargate infrastructure. In this role, you will own technical direction across CPU platforms, memory configurations, local and disaggregated storage systems, and their integration into large-scale AI clusters. You will evaluate vendor roadmaps, lead platform tradeoff decisions, and ensure compute and storage systems are optimized for training, inference, and supporting services. You will work cross-functionally with hardware engineering, performance modeling, networking, supply chain, and deployment teams, as well as external partners such as AMD, Intel, OEMs, ODMs, and storage vendors. This is a highly strategic role for someone who can operate deeply at the component level while also driving long-range infrastructure decisions. Key Responsibilities Own CPU and storage technical strategy for Stargate compute infrastructure across current and future generations. Evaluate CPU platforms across performance, efficiency, memory bandwidth, PCIe topology, cost, and roadmap alignment. Define storage architectures for AI environments, including boot media, local NVMe, shared storage, caching tiers, metadata services, and high-performance data pipelines. Drive server platform de

About the Team The Demo Studio is responsible for translating OpenAI’s most advanced capabilities into tangible, high-impact experiences for customers. We design and deliver the demos, applications, and environments that define how executives understand what is possible with AI. Our work sits at the intersection of product, engineering, design, and go-to-market. We operate as a hybrid of product studio and live production team, building experiences that are both technically credible and narratively compelling. About the Role We’re looking for a Demo Studio Lead to own the end-to-end demo experience for OpenAI’s major events, webinars, and strategic programs. This is a highly cross-functional role focused on translating cutting-edge AI capabilities into clear, compelling, and production-ready experiences. You will own the full demo portfolio for an event or initiative, spanning mainstage moments, breakout experiences, booths, and supporting content. You’ll define the narrative, architect workflows, build high-fidelity demo environments, direct presenters, and ensure flawless execution in live environments. This is not a traditional sales engineering, presentation, or narrowly scoped design role — it requires a combination of product thinking, technical fluency, storytelling, systems design, and operational excellence. A key part of the role is presenting the work directly: delivering live demonstrations to executive, technical, and industry audiences across mainstage, breakout, customer, and recorded settings. This role is ideal for someone who thrives in ambiguity, operates with strong ownership, and is excited about shaping how the world experiences AI firsthand. This is a hybrid role that can be based in either San Francisco or New York. In this role, you will: Own the end-to-end demo experience across OpenAI-hosted summits, webinars, third-party industry events, and strategic executive demonstrations. Translate approved product positioning, real OpenAI capabiliti

The Branch Manager SAFE Act is a senior management professional responsible for providing full leadership and direction to a team of employees, grow sales and client base in coordination with the consumer sales team . The overall objective of this role is to lead a team grow sales, build customer loyalty and recommend the development of business strategies or initiatives and may include the management of activities by external organizations, and the direct management of individuals and sales teams. Responsibilities: Develop a sales plans and drive individual production goals, including building referral network and relationships with internal partners and external contacts Create an environment through activity-based coaching and performance development and implement/execute coaching plan to develop employee’s skill set to achieve personal/branch goals Develop and execute integrated sales, relationship, and credit strategies that are aligned with the Retail Bank's priorities, execute business plan to achieve expected goals in all business categories Support portfolio growth by identifying opportunities to deepen relationships and increase client acquisition and ensure clients receive optimal service and monitor/adhere to operational controls Collaborate with branch partners to successfully achieve goals, build customer relationship and deliver customer service Leverage workforce planning tool to optimize staffing in branches and set expectations for branch staff, fostering an environment in which team members work together to achieve all business goals Integrate segment partners, partner with Assistant Manager and partner with the Division Operational to drive sales and drive outbound sales activities including: representing Citi and building partnerships in the community Conduct daily proof processes to ensure adherence to operational requirements; investigate control

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As a Product Engineer in Node Development group, you will be part of a forward-thinking team of engineers that solves complex problems to develop industry leading DRAM! You will engage on new technology at design start and be part of a team responsible for delivering technology to enable the full product portfolio, initial device qualification and production ramp. This will be accomplished through innovation and by cross-functional engagement with partner groups; Design, Test, Technology Development, Marketing, Manufacturing and Quality Assurance departments to co-optimize product and process. While you may not exhibit all of the characteristics/skills listed below today, we are highly interested in a teammate who is motivated to grow in technical breadth and depth. Suppose you are open to learning while being a valued member of a team of world-class engineers. In that case, we are determined to help build upon your existing foundation, while focusing on your individual and collaborative skills in this exciting and outstanding opportunity. Responsibilities Include: Enable new process node startup, qualification, yield, and ramp Collaborate with internal engineering groups; Design, Technology Development, Design for Test, and Quality teams to understand yield issues and priorities. Provide direction to development teams using thorough knowledge for process integration Develop and key metrics for feedback on a new technology Support design verification and validation using CAD tools and simulation

About the Team The Safety Systems org is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Safety Engineering team builds the platforms and tools that make OpenAI’s models safe to use in the real world. We partner closely with researchers, product teams, and policy to turn safety ideas into reliable, scalable systems: measuring risk, enforcing safeguards, and continuously improving how models behave in production. Our work sits at the intersection of product engineering, data, and AI, and directly shapes how millions of people experience OpenAI’s technology. About the Role We’re looking for a self-starter engineer who loves building products in an iterative, fast-moving environment—especially internal tools that unlock real-world impact. In this role, you’ll build full-stack tooling for our Safety Systems teams that directly improves the safety and reliability of OpenAI’s models, including in sensitive areas like mental health and other vulnerable-user protections. Your work will increase the team’s velocity in identifying and fixing safety issues and help tighten the feedback loop between policy, data, and the model training cycle. In this role, you will: Own the end-to-end development of internal tools that help improve the safety of OpenAI’s models (with a focus on areas like mental health and other vulnerable-user protections) Partner closely with Safety Systems researchers, engineers, and model policy creators to understand workflows, pain points, and requirements—and translate them into durable product solutions Build full-stack experiences to support core model policy workflows, such as labeling and inspecting data, analyzing and reviewing failure cases, and surfacing insights for iteration Optimize internal applications f

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Large Language Models (LLMs) continue to push the boundaries of what AI systems can do — but inference is still the bottleneck. The Model Efficiency team is responsible for pushing the limits of LLM inference efficiency across our foundation models. We explore and ship breakthroughs across the model execution stack, including: model architecture and MoE routing optimization decoding and inference-time algorithm improvements software/hardware co-design for GPU acceleration performance optimization without compromising model quality Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. As a Staff Research Engineer, you will develop, prototype, and deploy techniques that materially improve how fast and efficiently our models run in production. You may be a good fit

About the Team The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and startups. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. As an AI Deployment Engineer (ADE) in the OpenAI for Global Affairs team, you’ll help government and non-profit agencies transform their organization through solutions such as automated content generation, contextual search, and novel applications that make use of our newest, most exciting models and technology. About the Role OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe that achieving our goal requires effective engagement with public policy stakeholders and the broader community impacted by AI. The Global Affairs team builds authentic, collaborative relationships with public officials and the broader AI policymaking community to inform and support our shared work in these domains. We ensure that insights from policymakers inform our work and - in collaboration with our colleagues and external stakeholders - help shape policy guardrails, industry standards, and safe and beneficial development of AI tools. We are looking for an AI Deployment Engineer to collaborate directly with our Global Affairs team to help public sector actors unlock the benefits of OpenAI tools and products, aiming to broadly benefit humanity. This includes supporting a workforce organization deploying Certifications programs or advising a government partner on responsible implementation practices. Your role will integrate technical expertise with our mission to ensure that artificial general intelligence benefits all of humanity. In this role, you will: Technical Enablement & Deployment Serve as the primary technical advisor for Global Affairs partnersh

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a workspace for AI models to execute code, debug issues, and develop software just as human SWEs do. Our training environment for agentic models operates at an extremely high scale and has the flexibility to emulate any environment in which an agent might work. At the same time, our team builds and maintains OpenAI’s core platform for the deployment and execution of agents in production. Our systems power products such as Codex, Operator, tool use in ChatGPT, and future agentic products. Some of the most challenging technical problems in scaling the capabilities and utility of agents and agentic models lie in the infrastructure layer – and our team is focused on building the research and production systems that enable OpenAI to train the most capable models in the world, and maximize the utility of our agentic products for users around the world. About the Role As a Software Engineer on the Agent Infrastructure team, you will have the opportunity to work closely with both research and product at OpenAI - building and scaling systems to train highly capable agentic models, and building the platform and integrations to launch new agents to hundreds of millions of users worldwide. Your work will consist of both building new capabilities - standing up the infrastructure and integrations needed to train more complex agentic models - and rapidly scaling these new capabilities to some of the largest compute clusters in the world. At the same time, you’ll be instrumental to the launch of agentic products at OpenAI - building, maintaining, and scaling the production platform on which all agents run. We’re looking for people with deep experience building AI infrastructu

About the Team The Stargate organization is responsible for building and scaling the physical infrastructure systems that power OpenAI’s next generation of AI training and inference platforms. This includes the manufacturing, deployment, and operational execution required to bring large-scale compute infrastructure online globally. The team operates at the intersection of data center infrastructure, hardware manufacturing, supply chain, deployment operations, and systems planning. We partner closely across Infrastructure Strategy, Manufacturing Operations, Capacity Planning, Supply Chain, Deployment, and Engineering to execute one of the largest infrastructure scale-outs in the industry. About the Role We are seeking a Technical Program Manager, Rack Delivery to drive operational execution across rack manufacturing, site readiness, and deployment coordination for Stargate infrastructure programs. This role will serve as a key connective layer between manufacturing partners, deployment teams, and infrastructure readiness programs to ensure rack production and delivery timelines remain aligned with site availability and deployment sequencing. You will help manage operational execution across contract manufacturers (CMs), support build planning and RCCA processes, and coordinate deployment readiness across multiple concurrent infrastructure programs. You will also partner closely with Demand Planning teams to translate strategic planning inputs into actionable SKU-level manufacturing and delivery schedules. This role is ideal for someone who thrives operating across ambiguity, manufacturing operations, infrastructure deployment, and large-scale cross-functional execution. 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 support. Key Responsibilities Drive cross-functional coordination between rack manufacturing, deployment operations, and site readiness programs. Manage operational execution acros

About the team The Applied AI Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and startups. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to late-stage startups. About the Role We are seeking a technically proficient, business-minded Applied AI Engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, guiding them through ideation, development, delivery, and scaling to accelerate and maximize the value of what they build on our platform. You will have the opportunity to work on the most novel and creative use cases being built on our API, serving as a critical partner in collecting and delivering high-fidelity product and model feedback internally. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Startups Applied AI Lead. This role is based in our San Francisco or New York offices. 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 closely with strategic startup customers as their technical thought partner to build novel applications on our API, helping them rapidly move from ideation to scale. Provide proactive guidance to maximize business impact and accelerate application development. Experiment and prototype alongside customers, demonstrating practical use cases. Contribute to open-source resources and scale the function by sharing knowledge, codifying best practices, and publishing useful resources. Synthesize and deliver valuable feedback to the Product and Research

About The Team The Data Understanding team is responsible for creating the high quality datasets and their quantized representation for OpenAI. This includes synthesizing multimodal data, building VQ representations, and processing, filtering, deduplication, quality control, and tokenization so it can be used effectively in big model training runs. About The Role We’re looking to advance how OpenAI prepares, curates, synthesizes and understands multimodal data at scale. You’ll work on research and production problems like synthesizing multimodal content (images, audio, and video) and their supervisions, improving noisy data pipelines, building better quality filters, using models to automate data prep, and measuring whether changes in the dataset improve model performance. We Expect You To Have a strong track record of new or improved ML ideas, through publications, projects, or applied research. Own and drive a research agenda, from choosing the right multimodal data problems to carrying long-running work through to impact. Be excited by OpenAI’s empirical, collaborative approach to research. Nice To Have Experience with multimodal learning, audio, vision, video, synthetic data, or data-centric ML. Thoughtfulness about AI’s impact, including privacy, provenance, and data quality. Experience building high-performance deep learning or large-scale data processing systems. 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