Applied Ai Engineer in San Francisco

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Relevance & Personalization (R&P) team is Airbnb's matching intelligence engine — a talented team of ML engineers, applied researchers, and technical program managers who connect guests to the right listings across every surface and help hosts compete and thrive in our marketplace. We work at the intersection of search ranking, recommendations, personalization, and generative AI, and we're building toward a future where Airbnb feels less like a search engine and more like a knowledgeable travel companion that understands your needs across your entire trip journey. The Difference You Will Make: As Product Manager for Relevance & Personalization, you will help set the strategy and drive execution for some of Airbnb's highest-leverage AI systems. You'll own the roadmap and shape how personalization works across the guest journey, and help define how we close the feedback loop for hosts. You'll partner with engineers, researchers, designers, and cross-functional teams to ship systems that directly drive bookings, guest satisfaction, and host success — at global scale. A Typical Day: Define and drive the roadmap for Airbnb's relevance and personalization platform — from natural language query understanding to multi-turn, context-aware discovery experiences Make prioritization calls that balance multiple competing objectives: guest experience, host success, revenue, fairness, and marketplace health Partner with ML engineers and applied researchers to shape model strategy, evaluation frameworks, and experimentation design Align cross-functional partners — Guest, Host,

About the Team OpenAI’s Research Program Management team partners with researchers and engineers to advance the development of increasingly capable, safe, and beneficial AI systems. We work alongside teams developing our core models, helping turn ambitious research goals into coordinated execution across model training, alignment and safety, and research infrastructure. The team also regularly collaborates with our closest cross-functional partners such as Security, Applied product and engineering, Strategy, and Scaling. About the Role As a Research Program Manager, you will embed with research teams and help drive some of the most technically complex and consequential work behind OpenAI’s model development. Depending on your focus, your work may span training, reasoning, evaluations, compute, research infrastructure, safety, model launch readiness, and governance. You will translate evolving research priorities into actionable programs, help teams navigate technical and operational tradeoffs, and keep important work moving as new issues emerge. This is a hands-on technical role: you will engage directly with research workflows, experimental results, technical systems, and engineering constraints; not simply coordinate from the sidelines. 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. You might thrive in this role if you: Have 5+ years of experience in research program management, technical program management, or related roles in fast-moving environments. Can engage substantively with researchers and engineers on topics such as model training, experimental design, model safety, evaluation methods, data workflows, compute infrastructure, or distributed systems. Are comfortable working directly with technical tools, research data, experimental results, or operational workflows to understand problems and develop practical solutions. Have a strong track record of movi

About the Team OpenAI is a frontier AI research and deployment company. Frontier research is at the center of how we advance our mission, with researchers, engineers, product leaders, operators, and many other teams working together to turn new capabilities into systems that benefit humanity. The People team helps OpenAI attract, engage, and support the exceptional talent this work requires. Employer Brand sits at the intersection of Research, Recruiting, Communications, Marketing, and Brand. Its mandate is to continue to establish OpenAI in the talent market as the unique and leading frontier research lab—not simply another technology company—and make our distinctive research environment, mission, culture, and opportunity for impact relevant and tangible to every priority talent audience. About the Role We’re hiring an Employer Brand Manager to build and scale the strategy, narrative, and operating system that shape how priority talent understands OpenAI. This senior individual contributor will anchor our employer brand in OpenAI’s identity as a frontier research lab and translate an evidence-backed “why OpenAI / why now” narrative into campaigns, researcher and employee stories, recruiter and hiring manager enablement, and candidate experiences. This role is especially important as OpenAI competes for exceptional talent across research, engineering, product, and other mission-critical functions in a fast-moving field where external perceptions can be incomplete or change quickly. You will develop a clear, credible talent narrative for priority audiences—anchored in frontier research and substantiated by individual agency, world-class infrastructure, research-to-product translation, deployment scale, and a willingness to answer hard questions candidly. This role is responsible for ensuring the external brand resembles our culture and ethos internally, therefore must remain immersed in various OpenAI research and applied branches. This role is based in San Francisco

About the Team The Future of Computing Research team is an applied research team within the Consumer Devices group focused on developing new methods, models, and evaluation frameworks that support our vision for the future of computing. We work at the frontier of multimodal AI, helping turn emerging model capabilities into product experiences that are useful, delightful, and worthy of long-term trust. Our work explores a new class of AI systems that can learn over time, adapt to individuals, and support people in the flow of daily life. This includes long-term memory, user modeling, and personalization systems that are aligned not just with immediate satisfaction, but with a person’s broader goals, values, and well-being. We work closely across research, engineering, design, product, and safety to define what it means to build AI systems that know you over time, act at the right moment, and help in ways that are context-aware, respectful, and demonstrably beneficial. About the Role We are looking for a Research Engineer / Scientist to join the Future of Computing Research team to work on RLHF and post-training for personalized, multimodal AI systems. This role will focus on building the learning and evaluation foundations that help models become more context-aware, adaptive, and useful over time. You will work on problems such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that must make high-quality behavioral decisions in realistic user settings. The work is deeply product-grounded: success is not just higher benchmark performance, but better model behavior in real-world use. The ideal candidate is excited about pushing beyond one-turn assistant behavior toward systems that improve through feedback, learn from richer signals, and are trained against meaningful notions of user value. Internally, that maps closely to the need for careful reward design, feedback loops, and evaluation frameworks that test whether i

About the Team The Future of Computing Research team is an applied research team in the Consumer Devices group focused on developing new methods and models to support our vision as we advance forward in our mission of building AGI that benefits all of humanity. About the Role As a Technical Lead on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities. This role is based in San Francisco, CA. We follow a hybrid model with 3 days a week in the office and offer relocation assistance to new employees. In this role, you will: Evaluate and select silicon platforms (GPUs, NPUs, and specialized accelerators) for on-device and edge deployment of OpenAI models. Work closely with research teams to co-design model architectures that meet real-world deployment constraints such as latency, memory, power, and bandwidth. Analyze and model system performance, identifying tradeoffs between model design, memory hierarchy, compute throughput, and hardware capabilities. Partner with hardware vendors and internal infrastructure teams to bring up new accelerators and ensure efficient execution of transformer workloads. Build and lead a team of engineers responsible for implementing the low-level inference stack, including kernel development and runtime systems. Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of. You might thrive in this role if you: Have experience evaluating or deploying workloads on GPUs, NPUs, or other specialized accelerators. Understand the performance characteristics of transformer models, including attention, KV-cache behavior, and memory bandwidth requirements. Have designed or optimized high-performance compute systems, such as inference engines, distributed runtimes, or hardware-aware ML pipelines. Have experience building or leading teams work

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Operations Operations is the backbone of Brex’s mission to power businesses through our Intelligent Finance Platform. We own credit, fraud, money movement, and payments, protecting our customers and our company. From product operations that ensure flawless launches to scalable systems that drive innovation and precision, we operate at the intersection of product, design, engineering, and customer success. If you want to work at the heart of the business, Operations is where you belong. What You’ll Do Account Servicing owns what happens to a Brex account after it's live: money applied against statement balances, billing terms changed, auto-pay kept working, points debited and granted, credit performance reported to the bureaus, and accounts closed cleanly. We're hiring a manager to run that portfolio. You'll inherit a team with deep subject-matter expertise in specific queues, a set of in-flight migrations from other teams, and a

About the Role OpenAI’s Industrial Compute organization is responsible for ensuring our compute infrastructure scales efficiently to support millions of users and increasingly sophisticated AI models. We’re looking for a Data Scientist to partner closely with Capacity Systems Engineering, Infrastructure, Product, and Research to optimize inference capacity across our global GPU fleet. This role combines statistical modeling, large-scale data analysis, forecasting, and systems thinking to drive critical decisions around infrastructure investments, performance-efficiency trade-offs, and customer experience. You’ll transform complex operational data into actionable insights that directly influence how OpenAI allocates and scales one of the world’s largest AI compute environments. Key Responsibilities Build statistical and machine learning models to profile and improve GPU utilization, latency, throughput, and overall fleet efficiency. Develop forecasting models for inference demand across products, regions, and model families. Analyze production workloads to identify latency bottlenecks and capacity constraints, highlighting optimization opportunities. Partner with Capacity Systems Engineering to inform infrastructure planning and long-term GPU investment strategies. Design experiments and simulations to evaluate scheduling policies, serving strategies, and infrastructure tradeoffs. Build dashboards and operational metrics that enable leadership to make data-driven capacity decisions. Collaborate with Product, Research, Finance, and Infrastructure teams to align compute planning with business growth and model roadmaps. Communicate technical findings clearly to both engineering teams and executive leadership. Qualifications MS or PhD in Statistics, Computer Science, Operations Research, Applied Mathematics, Economics, or related quantitative discipline (or equivalent industry experience). 5+ years of experience working in the infrastructure data science space. Strong ex

About the Team OpenAI's Research Team is at the forefront of AI research, pushing the limits of what AI can achieve. Our team is dedicated to developing advanced AI systems that are powerful, safe, and beneficial for everyone. About the Role The Research IP Partnerships team is in need of Technical Program Managers (TPMs) to streamline the integration of our applied research with external strategic partners. This role is critical for synthesizing research from cross functional teams, enabling model deployment, and ensuring new technologies are effectively adopted. You will act as the connection that enables our partners to deploy the most advanced AI models. Your primary focus will be to increase our research velocity and ensure that our deployments are successful and collaborative with our partners. 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: Build and share a deep understanding of frontier AI model development Partner with internal and external teams to drive deployment of the latest OpenAI technologies Manage critical inquiries from both technical and non-technical partners Design and implement simple, scalable processes that solve complex problems Deliver high-profile pipeline and tooling projects on tight deadlines Work across research and engineering to align goals, streamline communication, and support business priorities You might thrive in this role if you: Have experience in a strategic partnerships and technical program management role Can right-size process to align stakeholders while ensuring speed of delivery (action-oriented) Are fantastic at building cross-functional relationships and having empathy for the many roles involved in deploying research Can design and build tools (via code / no-code / AI) to facilitate internal processes Are a great communicator across written, presentation, and visual forms. Are engaged and c

About the Team The Core Models team helps shape how OpenAI’s frontier models are built, measured, and launched. We work across Research, Engineering, Model Design, Data Science, and Product to turn advances in model capabilities into reliable, useful experiences for people. Our scope includes model planning and launches as well as building data flywheels, evaluations and measurement systems to ensure our models have strong capabilities and behavior. About the Role As a Product Manager for the Core Models team, you'll be at the forefront of defining and guiding the future of how our AI models work in real-world applications. You will connect user needs to model and systems decisions: how prompts are understood; how information is aggregated and made useful for training and evaluation data; and how capabilities move from research prototypes into the mainline model and launch stack. You will operate comfortably across research, infrastructure, and consumer product surfaces, creating clarity where ownership and technical boundaries are still emerging. 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: Translate user and product goals into clear model requirements, system architecture choices, and research priorities across query understanding, indexing, retrieval, ranking, tool boundaries, data, training, inference, and evaluation. Build closed learning loops that turn product usage, explicit feedback, and other user signals into datasets, evaluations, experiments, training priorities, and launch decisions. Define success across offline evaluations and online product metrics, balancing model quality, usefulness, latency, safety, reliability, and cost. Partner closely with post-training research, applied product engineering, Model Design, and Data Science to integrate capabilities into the mainline model stack. Create reusable platforms and operatin

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why This Role Is Different This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineeri

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why This Role Is Different This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineeri

About the team Special Situations at OpenAI is the company’s commercial engine for its most complex and consequential opportunities. The team operates where new verticals, partnership models, and customer motions must be invented, before a repeatable GTM or delivery playbook exists, by bringing together product, research, engineering, and GTM leaders around a single outcome. Many of these efforts begin as “new bets” (new verticals, new customer motions, new partnership models) and mature into repeatable ways of working that shape how OpenAI operates at scale. The team acts as a force-multiplier for the company by accelerating decision-making, aligning stakeholders, and converting complex opportunities into durable results. About the role We’re hiring a Deal Lead, Special Situations to help stand up new vertical bets, with a particular focus on partnership development in the semiconductor industry. You will identify where AI can create step-change value for semiconductor companies and ecosystem partners, originate and shape multi-project programs with FDEs and applied researchers, package them into compelling commercial proposals, and execute creative, complex partnerships while keeping executives and cross-functional teams tightly aligned. This role is especially focused on building strategic partnerships in semiconductors. You do not need to be a technical engineer, but you do need to be able to speak the language of the semiconductor industry, build credibility quickly with technical and business stakeholders, and come up the learning curve fast on industry dynamics, workflows, and constraints. A key part of the role is crafting deals with semiconductor companies that demonstrate our unique competitive advantages. To do this effectively, you will need to develop a strong point of view on the market, understand the competitive landscape, and clearly articulate OpenAI’s differentiated value and strategic advantage. Special Situations owns the overall success of each

About the Team OpenAI’s People team hires, engages, and retains world-class talent to safely build and deploy AGI that benefits all of humanity. The People Analytics team helps leaders make better, evidence-based talent decisions. About the Role As a People Research Scientist, you will bring deep expertise in research design, measurement, experimentation, and applied data science to OpenAI’s most important People programs. You will design studies, evaluate people processes, and help leaders better empower employees, strengthen organizational systems, and deliver exceptional employee experiences. This is a high-ownership individual contributor role combining hands-on research, methodological leadership, and scalable people science capabilities. We’re looking for an experienced researcher who can turn ambiguous People questions into rigorous designs, validated insights, and actionable recommendations. This role is based in San Francisco, CA or Mountain View, CA, with occasional travel to our San Francisco office. What You’ll Do: Design rigorous research and evaluation strategies for recruiting, organizational health, manager effectiveness, employee experience, and talent outcomes. Apply advanced statistical modeling, machine learning, and research methods to inform program design, evaluate effectiveness, and quantify business impact. Partner with People Operations, data engineering, and people systems teams to define data requirements, improve data quality, establish documentation standards, and ensure research datasets are governed, reproducible, and privacy-preserving. Build scalable people science infrastructure, including self-service agentic tools, automated validation workflows, reusable research datasets and analytical pipelines. Develop research playbooks that establish rigorous standards for study design, measurement, validation, and documentation, enabling high-quality, repeatable, and scalable research across the organization. Communicate findings through c

About the Team The SaaS and Software Governance team sits within Corporate IT and helps OpenAI scale from startup-speed tooling to mature enterprise architecture. The team owns practical governance for software, SaaS, integrations, APIs, identity, data access, and agent-enabled workflows, with a mandate to improve security, reduce software sprawl, and help business teams move faster through better foundations. About the Team OpenAI is scaling from an emerging, high-velocity startup into a mature enterprise operating model. The IT Software Architect will help shape the software, SaaS, Data integration, and agent-enabled architecture that lets the company move quickly while improving security, compliance, data quality, and customer, partner, and employee experience. This role is not a traditional ivory-tower architecture function. It is a hands-on governance and enablement role that partners with business teams, IT operations, Security, Procurement, Business Platforms, Applied teams and Data Engineering to guide software decisions, reduce unmanaged sprawl, and build reusable enterprise foundations. Why This Role Matters OpenAI’s software footprint is expanding rapidly across SaaS, internally built tools, agents, integrations, APIs, third-party platforms, and application systems that OpenAI. The company needs a stronger tools architecture layer that can help teams make good decisions early, avoid duplicate tools, govern sensitive data and identities, and identify where OpenAI should build instead of buy. The person in this role will help turn software governance from an approval checkpoint into an enterprise capability: a system that improves speed, reliability, security, and business outcomes. What You'll Do Own the target architecture for enterprise software, SaaS, integrations, APIs, and agent-enabled business systems across Corporate IT. Drive deprecation and consolidate targets for enterprise software. Build lightweight governance patterns that guide teams before

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 where more than half a billion people come to find what they love and build a life around it. That experience depends on deep understanding — understanding what a Pinner loves, what a Pin means, and how to surface the right content at the right moment. Across recommender systems, signals, and representation learning, the Applied Sciences team develops the next generation technologies that power personalized discovery across Pinterest. We’re looking for Staff Product Managers to help shape the next chapter of Pinterest’s applied AI/ML platform. In these roles, you’ll bring together research ambition and product discipline to help define the future of personalized experiences at one of the world’s leading discovery platforms. The roles Applied Sciences at Pinterest spans core areas including representation learning, signals, and recom