Ai Research Scientist Computer Vision in United States

About the Team The Privacy Engineering Team at OpenAI is committed to integrating privacy as a foundational element in OpenAI's mission of advancing Artificial General Intelligence (AGI). Our focus is on all OpenAI products and systems handling user data, striving to uphold the highest standards of data privacy and security. We build essential production services, develop novel privacy-preserving techniques, and equip cross-functional engineering and research partners with the necessary tools to ensure responsible data use. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing AGI that offers widespread benefits. About the Role As a part of the Privacy Engineering Team, you will work on the frontlines of safeguarding user data while ensuring the usability and efficiency of our AI systems. You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on investigating the interaction between privacy and machine learning, developing innovative techniques to improve data anonymization, and preventing model inversion and membership inference attacks. This position is located in San Francisco. Relocation assistance is available. In this role, you will: Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. Measure and strengthen model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks—balancing utility with provable guarantees. Develop internal libraries, evaluation suites, and documentation that make cutting-edge privacy techniques accessible to engineering and research teams. Lead deep-dive investigations into the privacy–performance trade-offs of large models, publishing insights that inform model-training and prod

About the Team The Codex Research team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of the Codex Research team, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measu

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. Our Communications team’s ethos is to support OpenAI’s mission and goals by clearly and authentically explaining our technology, values, and approach to safely building powerful AI. About the Role OpenAI is seeking an experienced communications professional to join our Platform & Research Communications team. This role will work closely with the Research Communications Lead and partner deeply with safety researchers, alignment researchers, and cross-functional teams to shape how OpenAI’s safety research is understood by researchers, journalists, policymakers, and the broader public. This position is responsible for developing and executing external communications strategies around OpenAI’s safety research—from alignment and evaluations to broader work that helps advance the safe development and deployment of increasingly capable AI systems. The ideal candidate brings strong science or technical fluency, excellent storytelling instincts, and experience helping researchers communicate complex work with clarity, accuracy, and nuance. You will partner closely with research leadership, individual researchers, policy, product, safety, legal, and cross-functional communications teams. This role requires both strategic judgment and hands-on execution in a fast-moving environment where research, public understanding, and high-stakes safety narratives intersect. This role is based in San Francisco, CA and follows a hybrid schedule (three days per week in office). Relocation assistance is available. In this role, you will: Shape Safety Research Narratives Develop clear, credible external narratives around OpenAI’s safety research, including alignment, evaluations, preparedness, interpretability, and other areas connected to the safe development of frontier AI. Translate complex technical work into accessible stories without oversimplifying, overstating impact

About the Team The Product Marketing team shapes how OpenAI brings its research, models, and products to market. We work across Research, Product, Engineering, Sales, Communications, and Marketing to translate technical advances into clear customer value, compelling market narratives, and go-to-market strategies that drive meaningful adoption. About the Role We’re looking for a senior product marketing leader to shape how OpenAI’s models and research are understood and adopted around the world. You’ll work directly with frontier research teams to understand emerging capabilities and translate them into compelling product strategies, market narratives, and customer experiences. Your scope will span frontier models, specialized models for cybersecurity and life sciences, multimodal capabilities, and the API portfolio that makes these systems accessible to developers and businesses. You’ll build and lead the team responsible for helping customers understand what our models can do, how they’re evolving, and how to deploy them responsibly. In this role, you will: Define the product marketing strategy for OpenAI’s models, research advances, and API portfolio. Embed with Research, Product, and Engineering to understand model capabilities, evaluations, limitations, and technical tradeoffs. Shape how OpenAI explains advances in AI to developers, business leaders, and the broader market. Lead positioning, launches, demonstrations, and adoption strategies across frontier, specialized, and multimodal models. Help customers navigate model selection, API access, privacy, security, and responsible deployment. Bring customer and market insights into research and product decisions. Partner with Sales, Solutions, Partnerships, and regional teams to develop customer narratives, use cases, and enablement. Work with Communications, Safety, Policy, and Legal to ensure technical claims are accurate and grounded. Build and lead a high-performing product marketing team and define success ac

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.

About the Team OpenAI’s mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Marketing team helps deeply understand customer audiences and market dynamics, influence the development of the right products, build sustainable and customer-aligned monetization models, and drive awareness, adoption, and usage across OpenAI’s products and platform. We take a data-driven approach to understand markets, develop monetization strategies, and uncover customer needs that shape product strategy and messaging. We partner closely with Sales, Partnerships, Product, Engineering, Research, Comms, and Design to deliver a cohesive end-to-end customer experience and lead go-to-market efforts for new product launches across channels. About the Role As a Product Marketing Manager, Research & Safety , you will shape how the world understands OpenAI’s frontier research and our approach to developing AI responsibly. You will establish the strategic narrative for some of the company’s most important research themes—including frontier capabilities, safety, preparedness, reasoning, and compute—and translate complex technical work into clear, credible stories for researchers, policymakers, and the broader public, working with cross-functional teams to translate that messaging and reach developers and enterprise. Working closely with Research, Safety Systems, Policy, Communications, and Product teams, you’ll lead the go-to-market strategy and messaging for major research and safety initiatives. You’ll develop narratives that build trust, translating technical concepts into tangible artifacts and messaging, drive industry understanding of emerging evaluation frameworks, and help communicate OpenAI’s unique perspective on responsible frontier AI development. You’ll also identify creative and non-traditional ways to bring these stories to the audiences that matter most. In this role, you will: Establish the strategic narrative f

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Product Manager , you will own GitLab's Secret Detection offering and the Vulnerability Research function that produces the detection content across security products. Secret Detection is one of the highest-signal, highest-volume security capabilities on the platform. Leaked credentials are the most common initial access vector in real breaches, and as AI agents write, commit, and configure more of the software, the surface area for exposed secrets grows faster than the number of humans watching it. You will own the full loop: detect a secret with high precision, tell the customer whether it i

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is on a mission to bring everyone the inspiration to create a life they love. The Applied Science team plays a critical role in this mission by developing cutting-edge machine learning solutions that scale across all of Pinterest engineering teams (see our team’s publications ). We're looking for a highly technical Engineering Manager with a deep understanding of modern recommendation systems to manage, lead and develop a team of machine learning researchers and engineers within the Applied Science team. In this role, you will help the team build a portfolio of work which can balance that addresses both immediate short-term business needs and long-term strategic breakthroughs. You will partner with senior leaders to evolve our technical roadmap and directly drive Pinterest’s core mission forward. W

ROLE SUMMARY As an AI-enabled strategic scientific leader, you will partner with Oncology Research Leadership to integrate AI-driven strategies that will drive data-informed decision-making across our Oncology Research pipeline. As the AI Portfolio Lead, you will bridge cutting-edge AI/advanced analytics with deep Oncology R&D expertise to guide our portfolio strategy. Working as an individual contributor reporting into the Head, Portfolio Strategy and Program Management, you will analyze and continuously assess Oncology Research projects using AI-driven insights (predictive models, scenario simulations, competitive intelligence) and propose actionable strategies to Oncology Research Leadership. This role is science-focused and spans across discovery and preclinical stage programs, ensuring that our project teams pursue the most promising scientific approaches and mechanisms of action. Your work will directly inform pipeline prioritization and resource allocation decisions, enhancing the quality and objectivity of governance deliberations with robust data. ROLE RESPONSIBILITIES Portfolio Analysis and Insights: Continuously analyze the oncology Research portfolio (ESD through Preclinical) using advanced AI/ML tools and analytics to evaluate each program’s scientific strength, probability of success, and strategic portfolio fit per disease area strategies. Strategy Recommendation: Develop and propose data-driven portfolio strategies (at both project and portfolio levels) to senior leaders and Research governance committee. Use scenario analysis and predictive modeling to highlight optimal project prioritization, pipeline balance, and resource allocation scenarios. AI-Enabled Decision Support: Integrate AI-derived insights (e.g. machine learning predictions, knowl

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role As a Research Engineer in OpenAI's Monetization Group, you will have the opportunity to work with some of the brightest minds in AI. You'll contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark. In this role, you will: Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. Optimize and Scale: Implement scalable data pipelines, optimize mod

Datadog is expanding the Technical Solutions (TS) organization by seeking a customer-focused, deeply technical Distinguished Architect to join our Product Solutions Architecture (PSA) team. In this role, you will act as a technical multiplier for the world's leading AI labs and AI-native companies. You will bridge the gap between their bleeding-edge infrastructure aspirations and Datadog’s technology roadmap, ensuring our platform natively solves the unique observability challenges of training and deploying foundational models at scale. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Leadership : Demonstrate thought leadership in the AI/LLM space. Influence key decision makers and stakeholders by connecting technical capabilities to organizational and business impact. Advisory : Strategically partner with highly technical Founders, Heads of Infrastructure, and Research Lead peers. Guide them on best practices and emerging industry trends in the AI/LLM space. Lead high-level technical and architectural conversations around AI adoption. Presentations : Lead deep-dive architecture reviews and design engagements with customer teams and their leaders to share industry trends, best practices, and demonstrate how Datadog can support high-throughput hyper scale AI workloads. GTM : Identify emerging AI-native technology shifts and feed them directly back to Datadog Product Management. Co-create custom observability integrations and solutions alongside Product SAs to keep Datadog at the absolute forefront of the AI stack. Collaboration : Collaborate with Product Solutions Architecture (PSA), Sales, Sales Engineering and Marketing in providing high-quality technical resources to a broad audience of practitioners and economic buyers. Hiring : Assis

AI Systems Engineer - Codex Core Agents About The Team The Codex Core Agents team builds the agent harness that turns model capability into real-world action. We own the systems around the model: prompting and interpreting model outputs, executing actions safely in real environments, and feeding production experience back into better models and better agent behavior. This team sits close to research and works across the stack: harness, model interaction, inference, sandboxed execution, orchestration, evals, production reliability, and the performance envelope around tokens, latency, cost, capacity, and quality. The harness is open source and increasingly part of how models are trained and evaluated, making this one of the highest-leverage layers in Codex. About The Role We’re looking for engineers to build the AI systems that make Codex agents dependable in production. The ideal candidate is an agent-systems builder: hands-on across low-level systems and ML workflows, able to debug Codex behavior end to end across the harness, model behavior, inference/runtime stack, GPU fleet, and product surface. You’ll work with research, infrastructure, and product to design agent harness capabilities, run experiments and ablations across the model + system prompt + harness stack, build frameworks for assessing production agent performance, and turn messy failures into durable improvements. What You’ll Do Design and build the core agent harness and execution loop that lets Codex agents interpret model outputs, use tools, execute code, and complete long-horizon tasks safely. Build sandboxing, isolation, orchestration, state, and workflow infrastructure for agents operating in real development environments. Develop evaluation, experimentation, and debugging systems that distinguish harness issues, model behavior, inference/runtime issues, and product failures. Run ablations across prompts, model-facing interfaces, context construction, tool-use strategies, and harness behavior to

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful, but useful, steerable, and reliable in practice. The job is not only to improve model behavior in isolation, but to turn those improvements into measurable gains in solve rate, usefulness, and economic value for users. What You’ll Do Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows. Work closely with research to develop and run evals to measure agent performance, regressions, failure modes, and edge cases. Improve performance through prompting, tool-use strategies, context construction, and model-facing experimentation. Analyze failures in production and systematically improve robustness and reliability. Build feedback loops and data systems that get better real-task data into evaluation and research. Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on. Help define what “good” looks like for agents completing complex tasks end-to-end. You Might Be a Good Fit If You Ha

Job Requisition ID # 26WD100617 Position Overview Autodesk is shaping the future of the design and make industries by helping our customers navigate a rapidly evolving AI-driven landscape. Supporting our Autodesk AI initiatives, you will help us understand how AI and new business models are reshaping the competitive landscape across Manufacturing, AECO (Architecture, Engineering, Construction, and Operations), and Media and Entertainment. This is an individual contributor role on a team with deep business, industry, and technical experience. A successful candidate builds with AI by default, not as a tool added on top. The way competitive intelligence gets done is changing faster than most business functions can adapt. We’re hiring for that gap. You will spend as much time building the systems that produce our intelligence as you will producing it. Location : We support hybrid work, and you work near our Portland, Oregon, or San Francisco, California offices. Responsibilities Build and maintain the automated systems that produce our intelligence, including source monitoring and refresh cadences Find the parts of our process that shouldn’t be manual anymore and fix them without waiting for permission Track how AI is changing our markets, following competitors, startups, funding, product releases, partnerships, research, talent movement, and regulatory shifts Work directly with business functions, product management, engineering, and technical benchmarking to define target markets, map competitive landscapes, size opportunities, identify gaps, and test market and com

We are seeking an exceptional, technically strong, and highly motivated Technical Product Manager to drive NVIDIA's healthcare Physical AI simulation platform. This is a rare opportunity to build foundational enabling technologies at the intersection of physical AI, robotics, simulation, and healthcare, redefining how leading healthcare device and robotics companies develop, train, evaluate, and deploy next-generation Physical AI systems. What You'll Be Doing: Bring innovative physics simulation to healthcare . Identify and integrate advances in physics simulation into enabling technologies that empower healthcare developers to build and validate solutions across robot learning, in-silicon product development, and in-silicon clinical trials—without owning the end applications themselves. Define the product vision and strategy for healthcare Physical AI simulation , spanning classical physics-based and generative simulation, and enabling developers to tackle some of the hardest challenges in healthcare on the path toward Physical AI and in-silicon product development. Develop PRDs with clear technical requirements, benchmarks, product metrics , and evaluation frameworks for simulation fidelity, scalability, policy performance, sim-to-real transfer, and developer efficiency. Lead cross-functional execution across research, engineering, product, developer relations, marketing, and business development to bring new simulation capabilities from research into open-source releases and production adoption. Drive early-access partnerships with healthcare developers, including robotics OEMs and MedTech companies. Translate partner requirements and feedback into detailed platform features and work closely with engineering to deliver them. Help build the horizontal NVIDIA