Research Intern in United States

About the Team The Future of Computing Research team is an applied research team within OpenAI’s Consumer Devices group. We study how AI systems perceive people and their surroundings, and we turn that research into capabilities for future products. Our work spans machine learning, sensing, and hardware, with a focus on building systems that work beyond controlled environments. About the Role We’re looking for a machine learning engineer to help shape how future AI systems understand the physical world and the people in it. The role focuses on multimodal perception and authentication, bringing together signals from cameras, microphones, and other sensors. You’ll work with specialized perception models and larger multimodal models, and partner with hardware, firmware, software, and product teams to bring new research into real-world systems. This role is based in San Francisco. We work in the office three days per week and offer relocation assistance. In this role, you will: Research and develop multimodal perception and authentication methods across visual, audio, and other sensing signals. Explore how specialized perception models and larger multimodal models can work together. Design data, training, and evaluation approaches that improve performance in real-world conditions. Study model behavior, robustness, and failure modes across sensing, data, and deployment environments. Integrate and validate new capabilities in real-time or resource-constrained systems. Work with hardware, firmware, software, and product teams to turn research into working systems. You might thrive in this role if you: Have a strong background in computer vision, audio or speech machine learning, multimodal learning, or sensing. Have experience developing specialized machine learning models, larger multimodal models, or both. Have brought research ideas into practical systems, prototypes, or products. Know how to design experiments, build evaluations, and investigate model behavior. Have wo

About the job Midjourney is an independent research lab exploring new mediums of thought and expanding the imaginative powers of the human species. We are a small, self-funded team focused on design, human infrastructure, and AI. Most of the products we build don’t have obvious precedents. We need product managers who can help teams navigate that uncertainty, make decisions, and turn ambitious ideas into products people can actually use. We’re looking for a Product Manager to help lead that effort. You’ll work closely with design, engineering, and research throughout the product development process, using tools like Claude Code to prototype concepts. You’ll help teams stay organized, make thoughtful decisions, and move projects from early ideation to launch. This is a hands-on role. Some days you’ll be writing product specs, running standups, and coordinating launches. Other days you’ll be interviewing users, reviewing prototypes, or digging into product questions that need deeper investigation. If you enjoy bringing structure to creative work and making it easier for great teams to do their best work, you’ll probably enjoy it here. What you’ll do Own the execution of major product initiatives. Partner closely with design and engineering from early exploration through launch. Write product requirements, manage backlogs, and keep projects moving. Facilitate planning, standups, reviews, and comms between teams. Help teams make informed decisions through UXR, research, and using Midjourney deeply yourself. Go deep on important product questions when needed, whether that means conducting user research, designing experiments, or working through a difficult product tradeoff. Help teams decide what matters most and make smart choices about quality, scope, and speed. You might be a fit if You’ve spent the last several years building software people love to use. You know how to create structure without weighing a team down. You’re as comfortable writing a product spec as you

About the job Midjourney is an independent research lab exploring new mediums of thought and expanding the imaginative powers of the human species. We are a small, self-funded team focused on design, human infrastructure, and AI. Most of the products we build don't have obvious precedents. We need a QA practice that helps us understand how they'll behave in the real world, identify problems early, and ship with confidence. You'll work closely with product, design, and engineering throughout development, helping teams identify problems early and ship with confidence. This isn't a role where you'll spend your days executing checklists. We expect you to think critically about how products behave, investigate difficult issues, improve how we test software, and go deep on the projects that matter most. If your favorite part of the job is making products noticeably better—and helping everyone around you build with more confidence—you'll probably enjoy it here. What you'll do Partner closely with product, design, and engineering throughout the development process. Stay close to the work by leading testing efforts on our most important product initiatives. Go deep on difficult problems—whether that's investigating a difficult bug, identifying edge cases, improving test coverage, or helping a team understand how a product behaves in the real world. Design thoughtful test plans and identify issues before they reach users. Help improve how we test software through better tooling, automation, and testing practices. Reproduce issues, identify root causes, and verify fixes before release. You might be a fit if You've spent the last several years testing software people actually use. You enjoy understanding how products behave, not just whether they work. You're as comfortable investigating a subtle bug as you are thinking through an entire user flow. You work well with designers, engineers, and product managers. You care about quality and believe the best testing happens througho

About the Team The Compute Strategy team works across research, engineering, product, finance, legal, and go-to-market teams to develop the partnerships, infrastructure capacity, and commercial models needed to advance AI infrastructure. About the Role As a member of the Compute Strategy team, you will develop commercial strategies for AI infrastructure partnerships and offerings. You’ll translate technical infrastructure opportunities into partnerships, transactions, and revenue. We’re looking for a commercially minded strategist who combines knowledge of semiconductors and AI infrastructure with strong financial judgment and the ability to execute complex partnerships. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Develop strategies for compute partnerships, vendor access, and infrastructure capacity. Structure and execute transactions with chipmakers, compute providers, and other infrastructure partners. Develop pricing frameworks and business cases for infrastructure-related partnerships. Evaluate partner technologies, strategic fit, commercial terms, and execution risks. Coordinate work across research, engineering, product, finance, legal, and go-to-market teams. Turn partnership learnings into repeatable operating models that can scale. You might thrive in this role if you: Have experience in strategy, corporate development, partnerships, or infrastructure transactions. Understand semiconductors and AI infrastructure. Can evaluate complex technical and commercial opportunities. Bring strong financial, analytical, and strategic judgment. Can influence and align technical and business stakeholders. Have negotiated or executed complex partnerships. Are comfortable operating in a fast-paced environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence ben

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

About the Team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to Semiconductor customers. You will own how solutions are scoped, built, shipped, and adopted across high-value engineering workflows such as RTL design, verification, and physical implementation. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will focus on the semiconductor vertical to deploy next-generation AI capabilities. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project m

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

About the team ​​Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security that could scale to an extreme level of severity. Our work involves: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. As we push toward AGI, cybersecurity becomes one of the most important and urgent frontiers: the same systems that can accelerate productivity can also accelerate exploitation. As a Researcher for cybersecurity risks, you will help design and implement an end-to-end mitigation stack to reduce severe cyber misuse across OpenAI’s products. This role requires strong technical depth and close cross-functional collaboration to ensure safeguards are enforceable, scalable, and effective. You’ll contribute directly to building protections that remain robust as products, model capabilities, and attacker behaviors evolve. In this role, you will: Design and implement mitigation components for model-enabled cybersecurity misuse—spanning prevention, monitoring, detection, and enforcement—under the guidance of senior technical and risk leadership. Integrate safeguards across product surfaces in partnership with product and engineering teams, helping ensure protections are consistent, low-latency, and scale with usage and new model capabilities. Evaluate technical trade-offs within the cybersecurity risk domain (coverage, latency, model util

About the team The Applied team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. 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: We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI! In this role, you will: Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse. Develop canonical datasets to track key product metrics including user growth, engagement, and revenue. Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions. Implement robust and fault-tolerant systems for data ingestion and processing. Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear. Ensure the security, integrity, and compliance of data according to industry and company standards. You might thrive in this role if you: Have 3+ years of experience as a data engineer and 8+ years of any software engineering experience(including data engineering). Proficiency in at least one programming language commonl

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

About the Team The ChatGPT team works across research, engineering, product, and design to bring OpenAI’s technology to the world. We seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, or platform barriers. Our commitment is to facilitate the use of AI to enhance lives, fostered by rigorous insights into how people use our products. About the Role We are looking for an experienced fullstack engineer to join our new ChatGPT Growth team to spearhead high-impact projects that amplify the user base of ChatGPT and Plus Subscribers. Your role will include projects such as optimizing account access, notifications, SEO, fostering value discovery, and virality. As we are in the nascent stages of growth at OpenAI, we will rely on you to discover pivotal areas where strategic bets or incremental efforts can catalyze significant impact. We value engineers who are impact-driven, autonomous, adept at discerning crucial insights from experimental results, and have a strong intuition for how to remove barriers to unlocking the magic of ChatGPT. In this role, you will: Drive long-term growth of ChatGPT through a combination of data analysis, product ideation, and experimentation to optimize product experiences. Plan and deploy backend APIs necessary to power these product experiences. Execute on projects by working closely with research, product, design, data science and other members of product teams to land impact on product goals. Create a diverse and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group-think. You might thrive in this role if you: Shipped features on web that optimize the user funnel, such as landing pages, product pages, purchase flows, search flows, etc. Are highly analytical and have experience designing and implementing A/B te

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 depl

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in San Francisco. W

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in NYC. We use a hy