You will:

• Backend Development and System Ownership: Design and implement secure, scalable backend systems for customers using modern, cloud-native AI infrastructure. Own services or systems, define long-term health goals, and improve the health of surrounding components.

• Collaboration and Standards: Collaborate with cross-functional teams to define and execute backend and infrastructure solutions tailored for secure environments. Enhance engineering standards, tooling, and processes to maintain high-quality outputs.

• Infrastructure Automation and Management: Write, maintain, and enhance Infrastructure as Code templates (e.g., Terraform, CloudFormation) for automated provisioning and management. Manage networking architecture, including secure VPCs, VPNs, load balancers, and firewalls, in cloud environments.

• Deployment and Scalability: Design and optimize CI/CD pipelines for efficient testing, building, and deployment processes. Scale and optimize containerized applications using orchestration platforms like Kubernetes to ensure high availability and reliability.

• Disaster Recovery and Hybrid Strategies: Develop and test disaster recovery plans with robust backups and failover mechanisms. Design and implement hybrid and multi-cloud strategies to support workloads across on-premises and multiple cloud providers.

Our ideal candidate has a strong engineering background, with a Bachelor’s degree in Computer Science, Mathematics, or a related quantitative field (or equivalent practical experience), and 5+ years of post-graduation engineering experience, with a focus on back-end systems and proficiency in at least one of Python, Typescript, Javascript, or C++.

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This means driving deployments from scoping through production, running the platform work that spans them, and working across API, Platform Foundations, Security, our cloud provider counterparts, and whoever else is on the critical path when dependencies and tradeoffs pile up.

Responsibilities:

• Own end-to-end program execution for Anthropic’s API across major cloud deployments, from scoping through production launch and steady-state operations

• Drive the platform programs that cut across individual deployments: the shared foundations that get built once and reused, not rebuilt per cloud

• Act as a primary coordination point with cloud provider counterparts, keeping engagement clean across multiple internal teams with touchpoints into the same partner

• Partner with engineering leadership to turn technical direction into executable plans with clear owners, dependencies, and risk tracking

• Build the program scaffolding (roadmaps, status reporting, decision logs, escalation paths) that lets a fast-moving org stay aligned without slowing down

• Drive the hard sequencing conversations when partner commitments, engineering bandwidth, and priorities are in tension, and surface them to leadership with a recommendation

• Identify where program coverage is thin relative to the load and help shape how we staff around it

You may be a good fit if you:

• Have 10+ years of technical program management experience, including ownership of large infrastructure or platform programs with many engineering teams and external partners in the mix

• Have deep technical fluency in cloud APIs, infrastructure, distributed systems, or platform engineering, enough to be a credible partner to senior engineers on architecture and sequencing, not just a tracker of their decisions

• Have run programs spanning organizational boundaries where you had no direct authority over most of the people whose work you depended on, and delivered anyway

• Have direct experience with multi-cloud or hybrid cloud environments, large-scale migrations, or building platform abstraction layers

• Have worked with major cloud providers (AWS, GCP, Azure) or similar large technology partners, and know how to keep those relationships productive when priorities diverge

• Are comfortable operating in ambiguity on the long arc while being ruthlessly concrete on what ships this quarter and who owns it

• Have a track record of making a program get cheaper to run the second and third time, not just landing the first instance

• Thrive in environments where the plan you wrote last month needs rewriting, without losing the thread on what matters

Strong candidates may also:

• Have experience with production serving infrastructure, inference systems, or ML platform work

• Have moved between senior IC and management roles, or have interest in doing so

• Have worked at a company rebuilding systems and org in flight during rapid scale-up

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Our backend teams cover a diverse range of domains, from core compute fabric resource management to service platforms and machine learning infrastructure.

Key responsibilities include:

• Building foundational infrastructure platforms that enable seamless operation across numerous geographic regions and cloud providers.

• Implementing cloud-agnostic infrastructure abstractions to help Databricks engineers more efficiently manage and operate their services.

• Developing tools and processes that drive engineering efficiency at Databricks.

We enhance the developer experience for Databricks engineers across various areas, including programming languages, linters, static analysis, IDEs, remote development environments, automated release pipelines, and test automation frameworks.

To be successful in this role, you will need:

• 2+ years of professional software development experience, or alternatively a PhD degree.

• Proficiency in one or more backend languages such as Java, Scala, or Go.

• Hands-on experience in developing and operating backend systems.

• Ability to contribute effectively throughout all project phases, from initial design and development to implementation and ongoing operations, with guidance from senior team members.

• Self-driven and passionate with a strong focus on delivering impact through team collaboration.

• Strong communication skills, both written and verbal, with the ability to produce clear technical documentation that drives alignment and decision-making.

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Our company is distributed by intention. We hire the best engineers we can find wherever they are, whoever they are. We collaborate across continents every day over email, GitHub, Zoom, and Slack. At our best, we write fast, scalable, intuitive, and high-quality software. We believe that the best way to do that is to empower individual engineers, code review every change, decide big things by consensus, and strive for incremental improvements.

As a Senior Software Developer, you will:

• Work with a globally distributed team of experienced engineers focused on data storage mechanisms and query capabilities of Elasticsearch.
• Be an expert in the storage engine area, and everyone will turn to you when they have a question about it. You'll improve those areas based on your questions and your instincts.
• Be a full-time Elasticsearch contributor, building data-intensive new features, fixing intriguing bugs, and increasing the testing coverage, all while making the code easier to understand.
• Design and implement advanced algorithms and data structures, often working at the system and hardware level. You’ll also engage with our global community for triaging and resolving issues and pull requests.

We're looking for someone with strong core Java skills and an excellent understanding of concurrent and parallel programming principles. You should have an excellent background in applied data processing (data structures, algorithms) and be familiar with storage systems and low-level abstractions in OS. You should also be able to work with a high level of autonomy and be able to take on projects and guide them from beginning to end.

This role does not have a variable compensation component. The typical starting salary range for new hires in this role is $128,300-$203,000 CAD. This role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched Registered Retirement Savings Plan (RRSP) with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being.

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This is a great fit if you care deeply about developer experience and want your engineering work to have outsized leverage: instead of shipping one feature, you're building the tools and systems that make dozens of features possible.

Responsibilities:

• Design and build shared UI components, libraries, and abstractions that product teams across Anthropic use to ship consistently and efficiently on web and mobile

• Contribute to the BFF API layer that powers Claude.ai's client applications,thinking carefully about clean contracts, performance, and reliability at the boundary between frontend and backend

• Improve developer velocity across the organization by reducing friction in our build, deploy, and testing pipelines

• Work on performance and reliability: identify and resolve latency issues, improve observability, and help establish high standards that the rest of the platform team can build on

• Partner closely with product engineering teams to understand their needs, unblock them when possible, and shape platform investments around where the most impact is

• Help maintain and evolve documentation and tooling that make the platform approachable for engineers joining or building on top of it

You may be a good fit if you:

• Have 5+ years of software engineering experience, with significant time spent building shared platforms, developer tools, or infrastructure that other engineers rely on

• Have strong practical skills in modern web technologies (React, TypeScript, Next.js) and experience designing or consuming APIs that serve frontend applications

• Care about developer experience and have a track record of building things that make other engineers more productive

• Have solid instincts around reliability, observability, and performance,and enjoy operationalizing those instincts in production systems

• Thrive in fast-paced, collaborative environments and enjoy working closely with cross-functional partners

• Pick up slack, even if it goes outside your job description

Strong candidates may also have experience with:

• Building shared component libraries or design systems for multiple surfaces (web, mobile, desktop)

• BFF architectures and API patterns that balance flexibility with consistency across client platforms

• Performance optimization and latency reduction in consumer-facing applications

• CI/CD, build systems, and deployment automation

• Observability and monitoring (metrics, logging, tracing)

• Working on AI/ML products or in rapidly evolving product environments

Candidates need not have:

• 100% of the skills needed to perform the job

• Formal certifications or education credentials

The annual compensation range for this role is $320,000-$405,000 USD.

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As an Engineering Manager in the infrastructure organization, you will lead the development of Stripe's Event Infrastructure, responsible for capturing, routing, and persisting billions of events daily.

Responsibilities

• Architect the Org & Culture: Design and scale a high-leverage org structure, defining what 'Elite Engineering' looks like and setting the bar for craftsmanship and operational rigor.
• Vision and Strategy: Define the scope, vision, and goals for your organization with little or no guidance from your manager, anticipating industry trends and influencing Stripe's long-range plans.
• Drive Operational Excellence: Instill a culture of rigorous thinking and meticulous craftsmanship, ensuring our infrastructure remains proactive and resilient as Stripe's business demands evolve.
• Bridge Engineering & Business: Collaborate with cross-functional leaders to align deep engineering needs with global business growth forecasts.
• Build the Future Team: Proactively invest in the development of the organization and its people at all levels, obsessing over talent and hiring and coaching other managers to elevate the skills of the leadership team.

Who You Are

We are looking for a visionary leader who thrives on operating Tier0 infrastructure and building world-class teams, equally comfortable in high-level strategic conversations and deep-diving into database internals.

Minimum Requirements

• Proven Leadership: Minimum 5 years of experience in a technical engineering management role, overseeing strategic projects.
• Systems Expertise: A deep technical background in distributed systems and experience operating Tier0 infrastructure at massive scale.
• Product Mindset: Ability to bridge deep engineering needs with global business growth forecasts and product strategy, specifically building abstractions that empower thousands of other developers.
• Strategic Navigator: Experience managing through ambiguity and making critical trade-offs between reliability, efficiency, and long-term architectural health.
• Curiosity and Humility: A deep curiosity about the 'nuts-and-bolts' of the business (e.g., global money movement) combined with the humility to continue learning and growing as a leader.
• Communication: Exceptional written and verbal communication skills.

Preferred Qualifications

• Scale and Infrastructure: Successfully shipped and operated critical infrastructure (database internals or related field) with significant responsibility over funds and/or critical data.
• Strategic Ambiguity: Ability to navigate complex, high-impact work where you must define your own scope and vision.
• Cross-Functional Influence: A track record of getting other teams on board with your vision to support execution in a way that benefits the broader company.

In-office expectations

In-Office: Stripe is a 'Live' culture. You will be expected to spend at least 50% of your time in your local hub to foster high-bandwidth, in-person collaboration.

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Responsibilities: Lead a team of talented engineers on the team, providing mentorship, guidance, and support to ensure their success. Partner with Engineering Managers to create roadmaps that deliver milestones toward a cohesive engineering vision. Understand user needs and pain points to prioritize engineering work and deliver high-quality solutions that meet user needs. Drive the execution of projects, overseeing the entire development lifecycle from planning to delivery, while maintaining high standards of quality and timely completion. Work with high-visibility teams and their stakeholders to support the Infrastructure's key engineering initiatives. Provide hands-on technical leadership (architecture/design, vision/direction/requirements setting, and incident response processes) for team members. Build amazing end-to-end API, developer experiences, and Stripe's public API infrastructure and tooling. Ensure our APIs are secure, reliable, and performant while solving product problems and building delightful API and developer experiences for our users. Building the future of the Stripe API and scaling Stripe's API Infrastructure while working with product teams to extend the capabilities of our APIs.

Requirements: 10+ years of technical experience or 7+ years in infrastructure/platform engineering field 5+ years in a strategic technical leadership role Experience leading engineering team(s) working on API design, abstractions, frameworks, or client libraries (e.g., building internal or external developer products). Hands-on experience building infrastructure and products for internal or external customers. Proven track record of delivering pragmatic solutions that accelerate business growth. Ability to adjust conversations from high-level discussions to detailed coding. Thrives on a high level of autonomy and responsibility. Clear and persuasive writing and in-person communication. Strong problem-solving skills, critical thinking, determination, and a growth mindset. Ability to work effectively with a diverse group of people, genuinely caring for each other and contributing to high-level psychological safety for all team members and partners. Proficient in at least one of the programming languages (Java, Ruby, Python, Go).

Preferred qualifications: Strong written and verbal communication skills for different audiences (leadership, users, company-wide). Experience with a variety of common infrastructure platforms (databases, logging, event streams, metrics, caching, etc). Experience leading partially remote teams. Experience developing sustainable, in-house framework and abstraction ecosystems in large engineering orgs. Experience building serverless platforms. Experience managing rigorous incident response processes and on-call rotations.

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The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the team

OpenAI’s Forward Deployed Engineering (FDE) org sits at the intersection of product, engineering, research, and go-to-market. We take frontier platform capabilities into the real world with design partners, turning raw customer signal into shipped software, repeatable patterns, and durable products.

About the role

Platform Engineer is a role within Forward Deployed Engineering (FDE) for strong software and ML engineers who want to build new platform capabilities from scratch, grounded in real customer deployments.

You will partner with customer-tagged FDEs who are driving delivery and customer outcomes, and embed where you can provide the highest leverage. In practice that means working in the trenches on architecture, product shaping, refactoring, hardening, and reusable abstractions, while preserving the pod’s ownership of customer understanding and day-to-day execution. You will also collaborate closely with our B2B Platform Team and other long-term owners to align early on what should generalize, what should remain customer-specific, and what “ready for handoff” looks like.

This role does not require travel. It is based in San Francisco or New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel is optional-by-project and typically <0%, with occasional spikes for key embeds or launches.

In this role you will

• Provide hands-on leverage to customer pods: embed with customer-tagged FDE teams to support generalization, contributing directly in architecture, product shaping, refactoring, and implementation.

• Turn repeated signals into platform bets: translate cross-customer patterns into crisp hypotheses with clear success criteria, scope, and a validation plan that fits real account constraints.

• Raise the engineering bar through tooling and mentorship: set org-wide quality norms through high-signal code review and pairing, and build lightweight developer tooling that makes good architecture, readability, and correctness the default across FDE.

• Collaborate as part of cross-functional platform teams: partner closely with B2B Product, customer-tagged FDEs, ops, and business partners to bring the right products and platform capabilities to market.

• Lead complex platform capabilities end-to-end when needed: for high-leverage primitives like our Context Platform, act as DRI from requirements through implementation, make key tradeoffs explicit, and pull in customer pods early to keep the work grounded in real deployments.

You might thrive in this role if you

• Bring 5+ years of software engineering or ML engineering experience with a track record of shipping 0→1 capabilities that other engineers or customers depend on. Experience in high-ambiguity, fast-iteration environments (startups or product-centric teams) is a plus.

• Have owned customer-adjacent technical work end-to-end, from scoping and hypothesis-setting through production adoption, and improved outcomes through structured iteration (instrumentation, evals, error analysis, and tightening success criteria over time).

• Have built or operated systems where reliability, security, and governance materially shaped design (permissions/RBAC, auditability, data access boundaries, rollout safety, observability, and incident-driven hardening).

• Communicate clearly across engineering, product, go-to-market, and executive audiences, simplifying complex ideas and translating technical tradeoffs into adoption impact, sequencing decisions, and measurable outcomes. You can credibly “pitch” a platform bet in a customer conversation.

• Default to systems thinking: you turn ambiguous feedback, failures, and escalations into durable product requirements and reusable platform capabilities, not one-off fixes or bespoke delivery work.

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.

Experience

5+ years of software engineering or ML engineering experience

Employment Type

Full-time

Workplace Type

Hybrid

Category

Engineering

Industry

Technology

Salary Range

$230K – $385K

Required Skills

• Software engineering
• ML engineering
• Architecture
• Product shaping
• Refactoring
• Hardening
• Reusable abstractions
• Systems thinking

Preferred Skills

• Experience in high-ambiguity, fast-iteration environments
• Customer-adjacent technical work
• Reliability, security, and governance
• Communication across engineering, product, go-to-market, and executive audiences

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The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform—from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources—compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need engineers who can navigate these platform differences, build robust abstractions that work across providers, and make smart infrastructure decisions that keep us cost-effective at massive scale.

Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards.

What You'll Do

• Design and build infrastructure that serves Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models
• Collaborate with CSP partner engineering teams to resolve operational issues, influence provider roadmaps, and stand up end-to-end serving on new cloud platforms
• Design and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions
• Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity
• Contribute to capacity planning and autoscaling strategies that dynamically match supply with demand across CSP validation and production workloads
• Optimize inference cost and performance across providers—designing workload placement and routing systems that direct requests to the most cost-effective accelerator and region
• Contribute to inference features that must work consistently across all platforms
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code or container orchestration
• Have strong interest in inference
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and self-driven, taking ownership of problems end-to-end with a bias toward flexibility and high-impact work
• Pick up slack, even when it goes outside your job description

Strong Candidates May Also Have Experience With

• Direct experience working with CSP partner teams to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings
• A background in building platform-agnostic tooling or abstraction layers that work across cloud providers
• Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments
• Strong familiarity with LLM inference optimization, batching, caching, and serving strategies
• Experience with Machine learning infrastructure including GPUs, TPUs, Trainium, or other AI accelerators
• Background designing and building CI/CD systems that automate deployment and validation across cloud environments
• Solid understanding of multi-region deployments, geographic routing, and global traffic management
• Proficiency in Python or Rust

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

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Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $295K – $555K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

OpenAI’s Inference team powers the deployment of our most advanced models - including our GPT models, 4o Image Generation, and Whisper - across a variety of platforms. Our work ensures these models are available, performant, and scalable in production, and we partner closely with Research to bring the next generation of models into the world. We're a small, fast-moving team of engineers focused on delivering a world-class developer experience while pushing the boundaries of what AI can do.

We’re expanding into multimodal inference, building the infrastructure needed to serve models that handle image, audio, and other non-text modalities. These workloads are inherently more heterogeneous and experimental, involving diverse model sizes and interactions, more complex input/output formats, and tighter coordination with product and research.

About the Role

We’re looking for a software engineer to help us serve OpenAI’s multimodal models at scale. You’ll be part of a small team responsible for building reliable, high-performance infrastructure for serving real-time audio, image, and other MM workloads in production.

This work is inherently cross-functional: you’ll collaborate directly with researchers training these models and with product teams defining new modalities of interaction. You'll build and optimize the systems that let users generate speech, understand images, and interact with models in ways far beyond text.

In this role, you will:

• Design and implement inference infrastructure for large-scale multimodal models.

• Optimize systems for high-throughput, low-latency delivery of image and audio inputs and outputs.

• Enable experimental research workflows to transition into reliable production services.

• Collaborate closely with researchers, infra teams, and product engineers to deploy state-of-the-art capabilities.

• Contribute to system-level improvements including GPU utilization, tensor parallelism, and hardware abstraction layers.

You might thrive in this role if you:

• Have experience building and scaling inference systems for LLMs or multimodal models.

• Have worked with GPU-based ML workloads and understand the performance dynamics of large models, especially with complex data like images or audio.

• Enjoy experimental, fast-evolving work and collaborating closely with research.

• Are comfortable dealing with systems that span networking, distributed compute, and high-throughput data handling.

• Have familiarity with inference tooling like vLLM, TensorRT-LLM, or custom model parallel systems.

• Own problems end-to-end and are excited to operate in ambiguous, fast-moving spaces.

Nice to Have:

• Experience working with image generation or audio synthesis models in production.

• Exposure to distributed ML training or system-efficient model design.

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.

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Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $250K – $380K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Workload team is responsible for designing and running OpenAI’s LLM training and inference infrastructure that powers frontier models at massive scale. Our systems unify how researchers train and serve models, abstracting away the complexity of performance, parallelism, and execution across vast GPU/accelerator fleets. By providing this foundation, the Workload team ensures that researchers can focus on advancing model capabilities while we handle the scale, efficiency, and reliability required to bring those models to life.

About the Role

We are looking for an engineer to design and implement the dataset infrastructure that powers OpenAI’s next-generation training stack. You will be responsible for building standardized dataset interfaces, scaling pipelines across thousands of GPUs, and proactively testing performance bottlenecks. In this role, you will collaborate closely with the multimodal researchers, and other infra groups to ensure datasets are unified, efficient, and easy to consume.

In this role, you will:

• Design and maintain standardized dataset APIs, including for multimodal (MM) data that cannot fit in memory.

• Build proactive testing and scale validation pipelines for dataset loading at GPU scale.

• Collaborate with teammates to integrate datasets seamlessly into training and inference pipelines, ensuring smooth adoption and a great user experience.

• Document and maintain dataset interfaces so they are discoverable, consistent, and easy for other teams to adopt.

• Establish safeguards and validation systems to ensure datasets remain reproducible and unchanged once standardized.

• Debug and resolve performance bottlenecks in distributed dataset loading (e.g., straggler systems slowing global training).

• Provide visualization and inspection tools to surface errors, bugs, or bottlenecks in datasets.

You might thrive in this role if you:

• Have strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure.

• Have experience building APIs, modular code, and scalable abstractions, while recognizing that abstractions ultimately serve the users and UX is an important part of the abstractions design.

• Are comfortable debugging bottlenecks across large fleets of machines.

• Take pride in building infrastructure that “just works,” and find joy in being the guardian of reliability and scale.

• Are collaborative, humble, and excited to own a foundational (if not glamorous) part of the ML stack.

Bonus points if you:

• Have background knowledge in data math, probability, or distributed data theory.

• Have worked with GPU-scale distributed systems or dataset scaling for real-time data

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.

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RTL & Codesign Engineer

Location

San Francisco

Employment Type

Full time

Department

Scaling

Compensation

• $225K – $445K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

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

We’re looking for a RTL Engineer to design and implement key compute, memory, and interconnect components for our custom AI accelerator. You’ll work closely with architecture, verification, physical design, and ML engineers to translate AI workloads into efficient hardware structures. This is a hands-on design role with significant ownership across definition, modeling, and implementation.

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:

• Produce clean, production-quality microarchitecture and RTL for major accelerator subsystems

• Contribute to architectural studies including performance modeling and feasibility analysis.

• Collaborate with software, simulator, and compiler teams to ensure hardware/software co-design and workload fit.

• Partner with DV and PD to ensure functional correctness, timing closure, area/power targets, and clean integration.

• Build and review performance and functional models to validate design intent.

• Participate in design reviews, documentation, and bring-up support across the full silicon lifecycle.

You Might Thrive In This Role If You Have:

• Graduate-level research or industry experience in computer architecture, AI/ML hardware–software co-design, including workload analysis, dataflow mapping, or accelerator algorithm optimization.

• Expertise writing production-quality RTL in Verilog/SystemVerilog, with a track record of delivering complex blocks to tape-out.

• Experience developing hardware design models or architectural simulators, ideally for AI/ML or high-performance compute systems.

• Familiarity with industry-standard design tools (lint, CDC/RDC, synthesis, STA) and methodologies.

• Ability to work cross-functionally with architecture, ML systems, compilers, and verification teams.

• Strong problem-solving skills and ability to think across abstraction layers, from algorithms to circuits.

• Passion for building industry-leading massive-scale hardware systems.

_To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations._

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.

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San Francisco

Employment Type

Full time

Department

Applied AI

Compensation

• $230K – $490K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses.

You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more.

We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth.

About the Role

The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably.

This role is based in San Francisco, CA.

In this role, you will:

• Design and build the development and production platforms that power our products, enabling reliability and security at scale

• Ensure our infrastructure can scale to the next order of magnitude

• Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think

• Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed.

You might thrive in this role if you:

• Have 5+ years building core infrastructure

• Have experience operating orchestration systems such as Kubernetes at scale

• Have experience building abstractions over cloud platforms

• Take pride in building and operating scalable, reliable, secure systems

• Are comfortable with ambiguity and rapid change

This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees.

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.

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What you'll do

• Work on the full rendering tech stack, top (tools, interface with script or other engine systems, etc.) to bottom (API invocation, shader authoring, etc.)
• Develop, optimise, and maintain rendering features and tools in a live game environment.

What you need

• Expert technical experience in C++, shaders, graphics APIs, graphics debugging tools
• Strong understanding of the graphics rendering pipeline
• Excellent 3D math skills
• Comfortable in a mature codebase
• Console programming experience
• 5+ years experience in games programming

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What you'll do

• Develop and maintain cross-platform graphics hardware abstraction layer for the Frostbite Engine.
• Develop and maintain tools to ensure high quality experience for render engineers using Frostbite.
• Work closely with game team engineers and the Frostbite rendering team to enable and deliver new rendering features.

What you need

• Strong C++ knowledge with at least 7 years of professional programming experience in real-time rendering.
• Experience working in rendering for multiple shipped titles on current-generation consoles (PS5, XBSX, PC).
• Knowledgeable of modern cpu/gpu hardware architecture.
• Significant experience using a low-level graphics API (DX12, Vulkan, console, etc).
• Significant experience with Graphics Debugging Tools (Pix, Renderdoc, console, etc).
• Deep understanding of memory management and multi-threading with related debugging and optimization experience.

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You'll support us in the conception and development of an innovative test field management system. Your tasks will include active participation in idea generation, requirement definition, planning, and implementation of solution possibilities. You'll get to know the test field in Weissach and participate in agile software development. You'll support the project leadership by attending regular meetings and writing requirements and testing software solutions. You'll communicate with various stakeholders to ensure smooth project execution.

What you need

You'll need a study place for vehicle technology, electrical engineering, mechanical engineering, business engineering, computer science, or a comparable course of study (at least in the 3rd semester or in the gap year between bachelor and master). You'll have programming knowledge, e.g., in Python, and knowledge of agile software development and project management tools (e.g., Jira). You'll have abstraction ability and analytical thinking, independent and structured working style, team and communication skills, and a safe handling of MS Office. You'll have very good German and good English skills (at least B2).

Why this matters

This role is a great opportunity to gain practical experience in a dynamic and innovative environment. You'll work on exciting projects and contribute to the development of new technologies. You'll have the chance to learn from experienced professionals and build a network of contacts in the industry.

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You'll develop a sustainable and user-oriented site strategy. Under consideration of dynamic requirements in the development department, the best possible working environments are designed and responsible investments are planned. The developed concepts are accompanied in close cooperation with the users and the central building, environmental and energy management until the realization phase.

• Analyse and evaluate site options
• Concept planning
• Operational floor management
• Creation of presentations and decision-making documents
• Planning and control of investment and capital flow plans
• Project management
• A wide range of interfaces in different departments of the company

What you need

• A place of study for engineering or business studies with a focus on building, architecture, project management or a comparable course of study (at least in the 3rd semester or in the gap year between bachelor and master)
• Good self- and time management
• Responsibility
• CAD knowledge (2D)
• Communication and abstraction skills
• Safe handling of MS Office
• Very good German and good English skills (min. B2)

Why this matters

This role keeps a world-championship-winning F1 team running. When equipment fails, races can be lost, so your work directly impacts performance. You'll develop deep expertise in high-spec facilities and have clear progression into senior facilities management roles. The F1 environment means you'll work with cutting-edge building systems and learn from the best in the industry.

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Your thematic focus will be on various vehicle projects, concept work for future models, a diverse range of topics, and evaluation of customer data. You will program tools (e.g., MATLAB, Excel, VBA) and engage in interdisciplinary exchange.

What you need

A study place for (business) engineering, vehicle technology, or a comparable course of study (at least in the 3rd semester or in the gap year between bachelor and master) is required. High automotive affinity, software and IT knowledge (e.g., MATLAB), abstraction ability, and analytical thinking are also necessary. A safe handling of MS Office (especially Excel and PowerPoint) and good English (B2) and very good German language skills are also required. A structured and independent way of working is also necessary.

Why this matters

This role is a 6-month internship. We offer individual support, diverse development opportunities, digital learning and working tools, mobile learning after coordination with the team, and an active internship community.

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