Production Operator Jobs

About the Team The AI Architect team partners with organizations to turn OpenAI's most capable models into meaningful, real-world impact. We work with customers across industries and digital-native businesses to identify where AI can create value, design secure and scalable solutions, and help those solutions move from early exploration into sustained production adoption. The team brings together technical strategy, customer partnership, and practical deployment expertise, working closely with Sales, Product, Engineering, Research, and specialist delivery teams. About the Role As an AI Architect, you will be the senior technical owner for a named portfolio of customers and the primary technical counterpart to their leadership teams. You will act as the “CTO of your book of business”, shaping each customer's AI strategy and guiding their journey from pre-sales discovery and solution evaluation through deployment, adoption, and measurable business impact. You will own the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex, and other agentic AI solutions. In partnership with the Account Director, you will translate business priorities into a focused use-case portfolio, an actionable adoption roadmap, and a clear path to durable customer value and growth. The Account Director owns commercial strategy; you own the technical strategy, customer journey, and path to production value. You will remain accountable for the technical outcome while bringing in the right specialists across deployment, implementation, enablement, security, product, and partners to provide deeper expertise and execute work where needed. This role calls for strong industry fluency, sound architectural judgment, and the ability to move confidently between executive strategy and hands-on technical conversations. In this role, you will: Serve as the primary technical advisor and long-term technical relationship owner for a named portfolio of existing customers and pre-sales prospect

About the Team The Consumer Products team at OpenAI builds the hardware that brings advanced AI technology directly into people’s hands. We design, engineer, and manufacture next-generation consumer devices that combine elegant design, robust engineering, and cutting-edge AI. Our team spans mechanical, electrical, and systems engineering — partnering closely with industrial design, operations, and software to create seamless, high-quality experiences that make AI more accessible and useful. About the Role As a Hardware Engineer on the Consumer Products team, you’ll contribute to the design, development, and integration of complex hardware systems for new AI-driven devices. You’ll work across disciplines to translate early product concepts into reliable, scalable, and beautifully crafted products ready for mass production. This role is based in Singapore. We follow a hybrid model (four days per week in the office) and offer relocation support for new employees. Occasional travel to manufacturing partners may be required. In this role, you will: Design, prototype, and validate mechanical and electrical subsystems from early development through mass production. Collaborate closely with design, operations, and manufacturing teams to ensure quality, reliability, and scalability. Drive DFM/DFA reviews, design iterations, and bring-up of prototype and pilot builds. Debug complex system-level issues and lead root-cause investigations and resolutions. Partner with global suppliers and cross-functional teams to ensure flawless execution from concept to launch. You might thrive in this role if you: Have 6+ years of experience in consumer hardware, consumer electronics, or advanced product development. Bring deep technical fluency in mechanical, electrical, or systems engineering (cross-disciplinary experience a plus). Have taken at least one consumer product from concept to mass production. Are energized by hands-on problem solving, iteration, and building in fast-paced enviro

About the Team The AI Deployment Management (ADM) team enables organizations to turn OpenAI products into real, sustained impact through world-class services execution. Our mission is to help customers successfully adopt and operationalize AI across their organizations. We partner with enterprises to translate the potential of OpenAI’s technology into durable capability - through structured training, technical enablement, and services. By helping customers move from experimentation to production, the ADM team accelerates time-to-value, deepens product adoption, and helps make OpenAI indispensable to how organizations work. About the Role The AI Deployment Manager role is a specialist post-sales enablement role focused on delivering high-impact enablement and adoption services across OpenAI’s product suite. This role is responsible for designing and delivering enablement experiences that support a repeatable adoption framework, driving sustained activation, expanding breadth and depth of usage, and measurable business value across OpenAI’s product suite, including ChatGPT Enterprise and Agents. This role blends strong product fluency, instructional design, and customer advisory. You will lead live workshops, deliver services, and design adoption interventions for audiences ranging from everyday business users to technical practitioners and executive leaders, helping customers understand not just what OpenAI’s products can do, but how to apply them effectively in real world workflows. Success in this role means accelerating customer confidence, increasing product adoption, supporting successful launches of new product capabilities, and helping customers translate product features into tangible outcomes across teams and business functions. You will own outcomes related to activation and sustained usage by shaping how enablement drives measurable customer impact. This role is based in our San Francisco office. We use a hybrid work model of 3 days in the office per week

About the Team The Synthetic RL team develops reinforcement learning methods that leverage synthetic data, environments, and feedback to train and evaluate frontier AI models. The team explores approaches such as self-play, simulators, and other synthetic evaluations to push model capability, generalization, and alignment beyond what is possible with the current prevailing methodology. About the Role As a Research Scientist on the Synthetic RL team, you will develop novel reinforcement learning techniques that use synthetic environments and feedback to improve large-scale models. You’ll work closely with other researchers to design experiments, analyze learning dynamics, and translate research insights into training approaches used in production systems. We’re looking for researchers who enjoy working on open-ended problems, value fast iteration, and want their work to directly shape how frontier models are trained. 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: Research and develop reinforcement learning algorithms Design and run experiments to study training dynamics and model behavior at scale Collaborate with engineers and researchers to integrate successful approaches into model training pipelines You might thrive in this role if you: Have a strong background in reinforcement learning, machine learning research, or related fields Have strong engineering and statistical analysis skills Enjoy exploring new problem spaces where data, objectives, and evaluation are imperfect or evolving Are motivated by seeing research ideas influence real-world AI 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 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 Training Runtime designs the core distributed runtime that powers everything from early research experiments to frontier-scale model runs. We work on building robust, scalable, high performance components to support our distributed training workloads. Our priorities are to maximize the productivity of our researchers and our hardware, with the goal of accelerating progress towards AGI. Within Training Runtime, the Process Management team develops the distributed OS responsible for launching, coordinating, and supervising the large numbers of processes that make up modern training workloads. Our runtime sits beneath training frameworks and on top of research infrastructure, ensuring jobs run reliably across massive clusters while maintaining performance, stability, and observability. Success for us is measured by both system reliability and researcher velocity - enabling ideas to scale from experiments to production training runs. About the Role As a Training Runtime: Process Management Engineer , you will work on the software that ties thousands of computers together and exposes them as a unified system. This system has to serve individual researchers running multiple parallel experiments, as well as our largest training runs spanning 100’s of thousands and even millions of machines and accelerators. This requires easy to use, introspectable systems that can promote a fast debugging and development cycle, as well as relentless optimization for scale while maintaining stability and performance throughout. You will work primarily in Rust , building high-performance asynchronous systems with a strong emphasis on performance, correctness, and scalability. Working at this scale and at the frontier of AI development poses novel challenges. Out-of-the-box approaches often don’t work. The problems you will be working on are highly ambiguous and require strong design judgment as well as proficient execution to advance the state of our infrastructure. We’re loo

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 AWS-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 AWS-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 hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration. You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You should enjoy working with external technical partners, extracting the real goal from messy requests, and pushing back or reframing when the requested experiment is not the highest-leverage path. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time. In this role, you will Partner with strategic customers and in

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 Applied AI Engineer, Digital Natives team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of frontier AI use cases for their industry and drive them to production through strong technical guidance. As an Applied AI Engineer in the Digital Native segment, you’ll help large and highly sophisticated companies transform their business through custom AI solutions applications such as customer service, automated content generation, contextual search, personalization, and other novel use cases leveraging OpenAI’s newest, most exciting models and latest capabilities. About the role We are looking for a driven solutions leader with a product mindset to partner with our customers and ensure they achieve tangible business value with frontier AI. You will pair with senior customer leaders to establish AI strategic roadmaps and identify the highest value applications. You’ll then partner with their engineering and product teams to move from prototype through production. You’ll take a holistic view of their needs and design an enterprise architecture using OpenAI APIs and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product. This role is based in our NYC office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Deeply embedded with our most sophisticated and technical platform customers, serving as their technical thought partner in ideating and building novel applications on our APIs. Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value. Experiment and prototype solutions with and for your customers. Forge and manage relationships wi

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model-powered scaled automated workforce and knowledge system that evolves and learns alongside a human workforce. By leveraging OpenAI’s state-of-the-art models and technologies, some already in production, others still in the lab, we develop systems that reason and work autonomously for a wide variety of operational work. We leverage real workloads for critical systems across finance, sales, customer support, integrity, product insights, internal operations, and more in order to drive insights into product and industry. We partner closely with internal teams and external customers globally, operating in a hyper-fast feedback loop where many of our users are just a few steps away. This proximity allows us to iterate quickly, validate impact in real time, and accelerate industry impacting learnings and systems builds. We are a highly multidisciplinary, self-contained team focused on transforming the workplace via smart systems, knowledge, scalable and reliable primitives that apply world-class AI capabilities across domains. Our mission is to learn fast and transform how humans collaborate with AI at scale. About the Role We are looking for a hands-on Engineering Manager to lead a small, fast-moving team building AI-powered automation systems that redefine how work gets done across OpenAI. This role sits at the intersection of applied AI, research, and product engineering. You’ll lead a team that builds systems that know how to learn from humans, and carry real workloads across, sales, support, finance, IT, and more, while staying deeply involved in the technical work. You will operate in a highly iterative environment, deploying systems directly to internal users, gathering rapid feedback, and evolving solutions in real time. This is a high-ownership role for someone excited about building 0→1 systems, working closely with customers, and shaping how AI transforms operational wor

About the Team The Consumer Products team at OpenAI brings groundbreaking AI technology to life through world-class hardware. Our Operations group ensures that every product moves seamlessly from concept to customer — integrating supply chain strategy, manufacturing operations, and quality systems to enable rapid, reliable, and scalable production. We partner closely with engineering, design, and manufacturing teams around the world to deliver exceptional products at launch and beyond. About the Role As an Operations Manager, you will own the execution and strategy that transforms early product concepts into high-quality, manufacturable consumer devices. You’ll lead cross-functional planning, manage vendor relationships, and ensure supply, cost, and schedule alignment across fast-moving hardware programs. This role is based in Singapore. We follow a hybrid model (four days per week in the office) and offer relocation support for new employees. Occasional travel to supplier and manufacturing sites is expected. In this role, you will: Develop and execute operations strategies that bridge product design and large-scale manufacturing. Drive build readiness and production planning from prototype through mass production. Partner with global suppliers to ensure materials, tooling, and capacity meet program goals. Collaborate with hardware, quality, and supply chain teams to establish and maintain robust operational systems. Track cost, yield, and schedule performance to ensure efficient and predictable product delivery. Build scalable processes that support rapid iteration and future product launches. You might thrive in this role if you: Have 6+ years of experience in hardware operations, manufacturing, or supply chain for consumer electronics or similar industries. Have successfully taken at least one product from concept through mass production. Are fluent in NPI processes, contract manufacturing dynamics, and global operations management. Bring strong analytical and co

About the team The Applied AI Engineer - Digital Natives team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of frontier AI use cases for their industry and drive them to production through strong technical guidance. As an Applied AI Engineer in the Digital Native segment, you’ll help large and highly sophisticated companies transform their business through custom AI solutions applications such as customer service, automated content generation, contextual search, personalization, and other novel use cases leveraging OpenAI’s newest, most exciting models and latest capabilities. About the role We are looking for a driven solutions leader with a product mindset to partner with our customers and ensure they achieve tangible business value with frontier AI. You will pair with senior customer leaders to establish AI strategic roadmaps and identify the highest value applications. You’ll then partner with their engineering and product teams to move from prototype through production. You’ll take a holistic view of their needs and design an enterprise architecture using OpenAI APIs and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product. This role is based in our SF or Seattle office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Deeply embedded with our most sophisticated and technical platform customers, serving as their technical thought partner in ideating and building novel applications on our APIs. Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value. Experiment and prototype solutions with and for your customers. Forge and manage relat

About the Team The Statsig team within OpenAI owns the experimentation, rollout, dynamic configuration, and analytics infrastructure that sits on the launch path for OpenAI products. Our systems help teams ship safely, evaluate product and model changes in production, and make high-confidence decisions from real-world usage. Statsig began as an independent company built around experimentation, feature management, and product analytics at scale. After Statsig joined OpenAI, the team began the next chapter: bringing that platform expertise and infrastructure into OpenAI as the experimentation and rollout foundation for every product we ship. This is infrastructure with a very direct product consequence. Teams working on ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and shared platform systems depend on Statsig to evaluate configurations, move traffic safely, ingest experiment data, serve analytics, and roll changes forward or back when production reality demands it. We are at a critical point in the platform journey. Adoption is accelerating quickly across OpenAI, and the systems that were already important are becoming load-bearing for how the company launches. The infrastructure needs to stay fast under sharply increasing evaluation volume, reliable when more services depend on it, observable enough to debug quickly, and efficient enough to support OpenAI-wide scale. Recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency across important services. The next phase is to make those gains systematic: a platform that can absorb rapidly growing product velocity while preserving low latency, data quality, operational safety, and developer trust. Based out of OpenAI's Bellevue office, we are a close-knit team that values in-person collaboration, technical depth, operational ownership, and building infrastructure that

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 Role As a member of the Data team within the Go-to-Market organization, you will help build a data-driven culture, improve decision-making, and advance strategic initiatives through analytics. This is a full-stack data role spanning data modeling, metric definition, visualization, analysis, and self-service tooling. You will build trusted, scalable data sources and products that give the business reliable, actionable insights. The work calls for judgment: you will choose the tool, approach, and level of investment that best fit each problem, from a focused analysis to a durable production data product. As a core partner to the GTM organization, you will address both foundational and ad hoc analytics needs. You will turn complex data into clear narratives that help technical and non-technical audiences understand what is happening, why it matters, and what they should do next. In this role, you will: Partner closely with GTM teams to proactively identify high-impact questions and translate business needs into data models, metrics, analyses, and scalable technical solutions. Define, source, validate, and operationalize the metrics that guide the business, helping teams incorporate them into planning and day-to-day decisions. Lead cross-functional data projects across established and emerging business areas, including setting the data strategy for greenfield domains. Build scalable data models and pipelines that integrate and transform data from multiple sources into trusted, accessible datasets. Create dashboards, reports, analytical tools, and other data products that enable stakeholders to answer questions independently. Own the lifecycle of metrics, analytical models, and data products from initial exploration and prototyping through production and ongoing maintenance. Choose the most effective approach for each problem—whether an analysis, metric, data model, visualization, or self-service product—based on the audience, urgency, complexity, and expected