Ai Research Fellowship in San Francisco

About the Team The DoorDash Research Fellowship is a 3-month program (extendable to 6 months) looking for Summer and Fall 2026 cohorts, for researchers and engineers who want to work on the hardest applied ML and AI problems in local commerce. Fellows are given the resources, autonomy, and access to real-world operational data needed to pursue ambitious research directions — with the goal of producing work that influences both the field and how DoorDash operates at scale. This program is modeled on the best external research fellowships: fellows are treated as independent researchers, not as junior employees on a product team. You pick the problem (within a set of priority areas), you own the direction, and you publish or ship the outcome. You’re excited about this opportunity because you will receive… Dedicated compute allocation sized to the research agenda — GPU clusters for training and inference budgets for experimentation Full access to DoorDash's research infrastructure — our internal RL stack, training and evaluation pipelines, RL environments built on real operational systems, agent evaluation harnesses, and the tooling our own research teams use day-to-day. Fellows are first-class users, not sandboxed visitors. Access to DoorDash operational data — real-world datasets spanning logistics, merchant operations, consumer behavior, and marketplace dynamics, under appropriate data governance Research mentorship from senior researchers and engineering leaders at DoorDash, plus a named research sponsor for each fellow who meets with you weekly and is accountable for unblocking your work Speaker series featuring leading researchers and practitioners from academia and industry — faculty from top ML programs, research leads from frontier AI labs, and senior operators from across tech. Fellows get dedicated 1:1 time with speakers when possible. A cohort of fellows working alongside you — a small, tight-knit group of researchers tackling different problems but sharing

Scale Labs, Research Scientist — AI Controls and Monitoring As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on AI Controls and Monitoring, you will design methods, systems, and experiments to ensure that advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. For example, you might: Develop monitoring techniques and observability methods that track AI behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs; Research mechanisms for layered control, including fail-safes, oversight protocols, and intervention methods that can halt or redirect AI systems when risks are detected; Design red-team simulations to probe weaknesses in oversight and control mechanisms, and build mitigations to close identified gaps; Collaborate with policymakers, engineers, and other researchers to establish standards and benchmarks for AI monitoring and escalation. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be

About the Team AI Research Lab is one of DoorDash’s frontier innovation hubs, focused on building the foundation for an AI-native future across our three core audiences: consumers, merchants, and dashers. As AI capabilities accelerate, the AI Research Lab operates at the center of technical exploration and real-world execution — connecting frontier model research, internal platform investments, operator teams, and strategic external partners. Our mission is to translate cutting-edge AI research into scalable, production-ready systems that drive measurable business impact. We combine deep technical rigor with strong operational execution to ensure that breakthrough capabilities become durable competitive advantages for DoorDash. About the Role As an Associate Manager, Strategy & Operations on our AI Research Lab, you will play a central role in converting frontier AI advancements into shipped products and scalable infrastructure. You will operate across research, product, and operations to move from early discovery and experimentation to deployment and impact. This role sits at the intersection of customer insight, technical innovation, and business execution. You will help define and scale the Lab’s most important bets while building the foundations that enable AI applications to compound over time. You’re Excited About This Opportunity Because You Will … Reimagining core experiences through AI, such as the merchant journey, by partnering directly with in-field merchants, sales, support, product, and engineering teams. You will help unify major initiatives into a coherent, AI-native interaction model. Own revenue-driving AI initiatives, operating as the accountable business owner for high-priority AI bets and ensuring clear linkage between technical progress and financial outcomes. Lead business planning cycles, developing go-to-market strategies for AI-powered products and capabilities, overseeing execution through structured project plans, resource allocation,

Scale Labs, Research Scientist — Agent Robustness As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them; Design and build harnesses to test AI agents’ tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment; Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use; Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and leveraging agent scaffolding, designing evaluation harnesses, an

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t

Scale Labs, Research Scientist — Safety Post Training As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties; Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations; Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generati

Scale Labs, Research Scientist — Frontier Risk Evaluations As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on Frontier Risk Evaluations, you will design and create evaluation measures, harnesses and datasets for measuring the risks posed by frontier AI systems. For example, you might do any or all of the following: Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities; Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems; Publish evaluation methodologies and write technical reports for policymakers. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and instrumenting ML pipelines, writing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes. A track record of published research in m

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world's most important decisions. The next frontier for AI is the physical world. We're looking for an AI Product Manager to own the Robotics vertical within our Physical AI team. In this role, you'll own both the development of the data and training environments (the teleoperated demonstrations, real-world collections, simulated tasks, and annotation products that labs use to train and evaluate robot policies) and the "data as a product" strategy that powers them. You'll understand where physical AI is headed, decide what robot tasks and embodiments are worth collecting, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside robotics or physical AI research, and is able to pair that domain understanding with a sense for where current robot policies succeed and fail in real-world workflows. You'll translate that expertise into datasets, environments, and evaluation frameworks that teach robots to do real physical work, and you'll be the domain expert Scale's most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You'll Do Own the Robotics AI roadmap & data strategy: Set product direction for the robotics training stack and the data strategy behind it — what data we collect, on which hardware and embodiments, and what we source internally vs. through our marketplace. Establish a vision for where physical AI is heading, driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading physical AI labs to understand where their robot p

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterpri

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world’s most important decisions. We’re looking for an AI Product Manager to own the Finance vertical within our Agents Data & Reinforcement Learning Environments team. In this role, you’ll own both the development of RL environments (the realistic, high-fidelity simulations of financial software and workflows that labs use to train and evaluate agents) and the “data as a product” strategy that powers them. You’ll understand where AI is being used in the Finance industry, decide what financial tasks are worth modeling, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside the Finance industry, and is able to pair that domain understanding with a sense for AI research and current agent capabilities in Finance workflows. You’ll translate that expertise into environments and datasets that teach AI agents to perform real financial work, and you’ll be the domain expert Scale’s most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You’ll Do Own the Finance AI roadmap & data strategy: Set product direction for the Finance agents training stack and the data strategy behind it. Establish a vision for where AI is continuing to transform the Finance industry (including investment banking, private equity, public markets, corporate finance, FP&A, etc), driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading AI labs to understand where their Finance agentic capabilities fall short and shape new product lines and competit

About Scale AI At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI) and building upon our prior model evaluation work with enterprise customers and governments to deepen our capabilities and offerings for public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce is some of the most critical work for how humanity will interact with AI. About Our FDE Team Generating high-quality data is the core problem our business solves. We aim to make producing and delivering high-quality data seamless and efficient for operators and customers. Our Team is building customer and operator-specific infrastructure to provide high-quality data with low turnaround time. You'll be exposed to the cutting edge of the Generative AI industry while directly interfacing with the leading model-building organizations in the space, including the top AI research labs and government agencies. Join us in shaping the future of Artificial General Intelligence. As a Forward Deployed Engineer, you'll be at the forefront of providing the critical data infrastructure that powers the most advanced AI models, directly influencing how humanity interacts with AI. You will work with the world’s leading AI companies and government agencies to solve their most complex AI data-related problems. Responsibilities: Drive Impact: Directly contribute to the advancement of AI by delivering critical data solutions for leading AI innovators and

At Scale, we believe that AI will dramatically improve the world, and our mission is to accelerate the development of AI. We’re looking for a Field Marketing and Events leader to continue to build and manage Scale’s robust Gen AI and Research field marketing and events program, including but not limited to Scale hosted executive events, Scale hosted practitioner events and meetups, research conferences, and our annual flagship conference, AI Leadership Summit. You will join a rapidly growing team with the opportunity to manage and execute events from start to finish, drive lead generation and pipeline growth, and plan event programming with the largest names in AI. The successful candidate will have a solid understanding of technology, model builder, and research markets, strong project management skills, a strategic mindset, ability to manage and grow a team, and a passion for AI & technology. You will: Own annual planning for all Gen AI and Research events including strategy and budget Establish event activities in line with sales goals and deal acceleration, prioritizing goals from the go-to-market leadership and business development teams on event location and audience Manage team of field marketing and events managers who will execute on planning and logistics. This role should have a player-coach mentality and ability to also execute on nuts to bolts planning for all executive dinners, meetups, happy hours, sponsored trade shows, and hosted conferences Manage contractor relationships including event production firms and outside vendors, and event budgets Align with growth marketing on marketing campaigns and marketing qualified lead (MQL) reporting Track event campaign performance, measuring ROI, results, and metrics through Salesforce and own any course correction for events that are not performing Own all aspects of Scale hosted conference, Scale AI Base Camp, including venue selection, vendor management, logistics, speaker

About the role The world is moving fast — and AI is moving faster. As a Product Marketing Manager focused on AI at Sigma, you'll be at the tip of the spear, helping define how we tell the story of one of the most exciting areas of the product. This role is as much about clarity as it is about creativity: you'll take complex, fast-evolving AI capabilities and distill them into the market messages, sales narratives, and customer stories that make people say "I get it — and I want it." We're looking for someone with genuine intellectual curiosity about AI, a bias for action, and exceptional instincts for what makes a message land. If you can absorb a lot of information quickly, find the signal in the noise, and write messaging that moves people — this role is for you. What you'll do Develop and refine positioning and messaging for Sigma's AI features, working closely with the Director of Product Marketing, AI and the Product team. Create sales enablement content — one-pagers, battlecards, demo guides, and objection handlers — that help the field confidently sell Sigma's AI capabilities. Support product launches for AI features: coordinate across product, design, marketing, and sales to bring new capabilities to market clearly and effectively. Research competitors' AI positioning and identify opportunities to sharpen Sigma's differentiation. Write and contribute to thought leadership content, blog posts, and customer-facing collateral that educate the market on Sigma's AI vision. Gather and synthesize customer and prospect insights — from win/loss data, customer interviews, and sales calls — to continuously improve messaging. Partner with demand generation and content teams to ensure AI messaging is consistently represented across campaigns, website, and events. What we're looking for 3+ years of product marketing experience in B2B enterprise software and/or cloud data platforms. The ability to learn quickly and deeply — you can get up to speed on a new te

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About The Role Snorkel is hiring a Head of Security to build and lead our security function end-to-end — infrastructure security, application security, and governance, risk & compliance (GRC). You'll own the security function end-to-end — strategy, team, and execution — and operate as the primary security voice with customers, auditors, and the exec team. You'll report to the CTO. This is a builder's role: you'll take security from its current state to a mature, right-sized function as Snorkel scales, hiring and developing the team as needs grow. Key Responsibilities Security Leadership & Team Building Define Snorkel's overall security strategy,