Data Operations Lead in San Francisco

About the Team Full Stack engineers within the Fleet Scheduling team are dedicated to building intuitive and scalable interfaces that empower researchers to efficiently manage AI workloads across some of the largest supercomputers in the world. Our focus is on developing robust, high-performance systems that provide real-time insights, resource tracking, and seamless interaction with complex infrastructure. We aim to optimize resource allocation, minimize operational overhead, and create user-friendly tools that enhance researcher productivity and system transparency. About the Role You will design, develop, and operate web-based systems that provide a powerful and intuitive interface to OpenAI’s supercomputing clusters. You will collaborate closely with researcher, product and infrastructure teams to deliver scalable solutions that enable seamless monitoring, job scheduling, and resource management. This is an opportunity to work at the cutting edge of AI infrastructure, designing tools that scale to exascale workloads while maintaining usability and performance. 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: Design and develop full-stack web applications to track, monitor, and manage large-scale AI workloads in real time. Collaborate with researchers and infrastructure teams to translate complex operational needs into intuitive UIs and scalable backends. Build data visualization tools (e.g., Gantt charts, dashboards) to provide insights into job scheduling and resource allocation. Optimize backend services to handle massive data throughput while ensuring low-latency performance and high availability. Implement frontend components that provide seamless interactions with scheduling, storage, and compute systems. Ensure system security, reliability, and scalability across globally distributed supercomputing infrastructure. You might thrive i

About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI’s research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You’ll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: Build and operate storage services that underpin OpenAI’s research infrastructure Develop object storage systems across cloud and in-house environments Build systems for cross-region data movement, replication, and recovery Design lifecycle management capabilities that keep data durable, available, and cost-effective Evolve the federation layer that unifies multiple backend systems behind a simple interface Improve performance, reliability, and operational excellence across the platform Collaborate closely with researchers and infrastructure teams to support rapidly evolving workloads You might thrive in this role if you: Have experience building or operating distributed systems in production Have worked on storage infrastructure, object stores, dist

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 Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. The Opportunity: Flexport IT is looking for a Senior Systems Engineer (Identity & Access) . In this role, you will design, implement, and administer our Identity and Access Management (IAM) solutions to ensure secure, efficient user lifecycle management. While you are our resident Okta expert, you are also a high-level IT generalist. You will oversee our broader SaaS ecosystem (Google Workspace, Slack, Jira) and endpoint management infrastructure (Jamf, Intune). Your expertise will drive automation, protect sensitive data, mitigate security risks, and maintain compliance in a heavily regulated industry. You will continually strive towards automation of toil. If you are still manually doing the same operational tasks 18 months from now, something has gone wrong. Flexport’s book of business is growing fast, but the promise of technology is that we can grow our business faster than our headcount. The automation you build will be a key factor in that effort. You Will IAM Architecture: Design, implement, and maintain the end-to-end lifecycle of Identity and Access Management platforms. Okta & Directory Trust: Administer Okta, directory services, Multi-Fact

What you’ll do Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy. Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements. Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks. Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation. Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes. What we’re looking for Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains. Ability to move fluidly between research prototypes and production-quality systems. Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility. A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.) Useful experience ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints. Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts. A background in computational physics or scientific computing. Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging. Experience in Agentic-SciML is a plus. Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines. Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Secure Manufacturing & Stealth (SMS) team protects OpenAI’s most sensitive product, manufacturing, launch, and partnership work from theft, leakage, espionage, and unauthorized disclosure. We operate across physical, digital, human, and third-party domains, building practical protections that allow teams to move quickly while preserving strict need-to-know controls. About the Role We are seeking a senior Secure Manufacturing & Stealth Partner to serve as the dedicated SMS owner for Marketing. This person will build trusted relationships across Marketing, understand launches and sensitive information flows, identify secrecy risks early, and embed practical controls into planning, creative production, events, agencies, vendors, media, and executive communications. The role owns the Marketing relationship while coordinating shared SMS capabilities when investigative, prototype-handling, regional, or other specialist support is needed. In this role you will: Serve as the primary SMS Partner and trusted adviser to Marketing, building a deep understanding of its priorities, planning cycles, launches, events, external partners, and sensitive information flows. Identify secrecy and information-exposure risks early, then translate SMS requirements into practical controls that protect sensitive work without unnecessarily slowing execution. Build, document, and socialize durable operating mechanisms for compartmentalization, need-to-know access, agencies and vendors, sensitive creative production, events, demonstrations, launch preparation, codenames, watermarking, and password controls. Assess and approve Marketing systems and information workflows, identify gaps or duplication, establish secure handling requirements, and advise AI-native Marketing initiatives on permissions, data governance, and operational tracking. Coordinate

About the Team Our Cyber team builds AI systems and products that help trusted defenders understand and respond to cyber threats while improving the safety and reliability of frontier models in security-sensitive settings. The team works across product engineering, model training, evaluations, safeguards, and deployment to make advanced cyber capabilities useful to defenders and responsibly managed. We collaborate closely with Safety/Preparedness, Research, Security, Legal, Communications, GTM, and external partners across OpenAI’s broader cyber work. About the Role We’re looking for research and software engineers to join Codex Cyber. You’ll help define and ship security products, work with trusted defenders and customers, shape model training and access patterns, and build research and evaluation systems for assessing cyber capabilities, validating safeguards, and improving training data. This role is hands-on and cross-functional, connecting product launches, model development, safety work, and real-world security use cases. In this role, you will: Help define and execute the technical roadmap for Codex Cyber’s security products, including evaluations, safeguards, trusted-defender workflows, and deployment decisions. Work with trusted defenders, customers, and partner teams to understand cyber use cases, evaluate risk, and turn feedback into product and research priorities. Shape cyber-specific model training and access patterns, including data, evaluations, validation, and deployment criteria. Build and validate systems for measuring cyber capabilities, monitoring misuse risk, and proving safeguards work in practice. Collaborate with Safety/Preparedness, Research, Security, Legal, Communications, Go-to-Market, and external partners on company-wide cyber priorities. Translate frontier cyber research into launch-ready tools, operational playbooks, and durable infrastructure for Codex and security products. You might thrive in this role if you: Enjoy 0 -> 1 envi

About the Team The Agent Post-Training 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 Agent Post-Training, 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, meas

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

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role We’re looking for an AI Applications Engineer to help drive Notion’s business transformation efforts. In this role, you’ll be a strategic partner to our internal stakeholders (primarily GTM, Finance and People teams) and deliver and scale creative AI-driven solutions to multi-faceted problems with measurable business impact. You’ll also build reusable components, evaluation patterns, and operational guardrails that make AI delivery repeatable across teams. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You’ll Achieve Work with stakeholders to discover opportunities from ambiguous problem statements, translate them into scoped solutions, and drive iterative releases from idea to adoption Build and ship end‑to‑end AI solutions—from problem framing through data readiness, modeling, evaluation, and production rollout Establish evaluation and production-readiness patterns (met

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 . We’re looking for a principal software engineer to lead the next generation of data infrastructure at Pinterest which powers mission critical big data and AI applications. You’ll be working on some of the most exciting big data and AI open source technologies (Flink, Spark, Kubernetes, etc.), at the scale of exabytes of data to help Pinners discover and do what they love. What you’ll do: Lead the strategy and technical direction of Pinterest’s data infrastructure for big data and AI applications Build and scale data infra frameworks and infrastructure to process petabytes-scale datasets, including compute engines, job management, resource management, scheduling and remote shuffling Work with internal customers on critical business use cases that rely on big data Provide thought leadership to the entire company on how data should be

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Senior Data Scientist - Network Value (Credit) The Network Value Data Science team is helping Plaid build an industry-leading fintech consumer network with best-in-class products and user experiences. We are a product analytics team embedded in key product areas across Plaid. We support some of Plaid’s most important OKRs and help execute on product roadmaps. We translate ambiguous product questions into tractable analysis, serve as analytical thought partners throughout the org, identify opportunities to build better products, and champion a data-first decision-making approach everywhere we go. You’ll be a Data Scientist supporting Credit, a critical product area within Plaid’s Network Value portfolio. You’ll become a data and analytical thought partner to product managers, engineers, and cross-functional stakeholders, helping shape Credit product strategy, improve product performance and user experience, and grow Plaid’s consumer network. You’ll translate business questions into analytics projects, perform ad-hoc and strategic analysis, improve visibility into core systems through data modeling and dashboarding, create OKRs and KPIs tied to business goals and user experiences, a

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. This internship will take place from January 25 - April 16 and you will need to be able to work out of our SF office during this time. What You'll Achieve: Conduct data analyses to gain insights about Notion and use these insights to uncover opportunities for improvements in our product and business. Communicate these insights with actionable recommendations to cross-functional teams (insights are useful, impact is even better!). Work with cross-functional partners across the product and business to learn about their functions and use data to advance their respective areas. Create metrics and build dashboards to monitor the growth and health of Notion. Communicate insights and recommendations effectively to leadership and have an impact on strategic decision-making. Qualifications: Pursuing a bachelor's or master's in a quantitative field such as Economics, Statistics, Applied Math, Engineering, Computer Science, or Natural Sciences. Must graduate before December 2027. This internship will take place from January 25 - April 16 and you will need to be able to work out of our SF office during this time. Previous research or internship

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? We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a Data Scientist on our Analytics and Data Insights team, you'll work on problems that don't have textbook answers yet; building the analytics that shape product and company strategy, designing the experiments that prove or kill our biggest bets, and helping enterprise customers understand what foundational AI actually means for their bottom line. You'll own analytical work end-to-end: from framing the right questions and building the models to shipping insights, tools, and results that product leaders, sales teams, and enterprise customers rely on. As a Data Scientist, you will: Drive the mission forward. Build bleeding-edge agentic analytics: Agentic analytics is far from a solved problem, and we want to be the company that solves it. We need the sharpest minds with the curiosity, drive, and focus required to build the tools necessary to bring order and clarity to real world data. Define AI impact measurement: own the end-to-end analytics st

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! Prior to applying please note: We are currently unable to provide visa sponsorship for this position (including H-1B, OPT, F1, CPT or other employment-based visas). Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. This role is hybrid requiring 2 days in office at our San Francisco hub every Tuesday & Wednesday (located at 130 Sutter St, San Francisco, CA). About the Role We're hiring a Senior Data Engineer to build the data foundation for a new discovery-stage team focused on Taskrabbit client retention and personalization. The team's mandate is to turn our biggest unaddressed retention bet — predicting what home service a client will need and when, then reaching them proactively — from concept into validated, in-market tests. You'll be one of four new hires on a small, cross-functional pod (Product, Design, Marketing, BizOps, Machine Learning, and E