Research Analyst 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

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

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's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity,

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

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 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! In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand. The role Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it. What you'll work on Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating. AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution. Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other

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 the Role Snorkel AI is looking for a Head of Talent Acquisition Operations & Insights to build and lead the systems, processes, tools, metrics, and operational infrastructure that power our recruiting organization. This leader will own the design and execution of a modern TA operations function that enables Snorkel AI to scale hiring with speed, quality, consistency, and data-driven decision-making. This is a builder role for someone who has stood up TA operations in a hyper-growth technical startup environment. You should be equally comfortable designing the strategy, implementing the systems, improving process, building reporting, leading recruiting coordination, and partnering with recruiting and business leaders to improve how hiring gets done. We are looking for someone who brings strong operational discipline, deep knowledge of recruiting systems and workflows, and a forward-looking perspective on how AI can modernize talent acquisition. What You’ll Do Build and lead the TA operations function for Snorkel AI, including recruiting systems, tools, workflows, reporting, process, and coordination. Own the recruiting tech stack, including ATS configu

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 the Team Marketing at Snorkel is growing rapidly and anchored by high-ownership operators who lead independently, align cross-functionally, and consistently deliver outsized results. We partner across Sales, Product, Research, and the executive team to translate complex AI and data value into differentiated positioning, integrated programs, and field-ready enablement that accelerates growth. The culture is high standards, high autonomy, and high collaboration. About the Role Reporting to the Sr. Director of Product Marketing, the Product Marketing Manager, Frontier Labs will own the GTM execution for our frontier lab business. You will partner closely with Research, FDE, and frontier-facing sales teams to translate technical work into research-credible positioning, repeatable sales plays, and high-quality GTM programs that resonate with research and procurement leaders inside frontier labs. You will keep the frontier asset library (battlecards, technical one-pagers, decks, benchmark and eval narratives) sharp against a fast-moving market, and bring competitive and customer insight into every motion. This is a hands-on role for a product marketer who wants

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,

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! Counsel, Commercial What You’ll Do Snorkel AI is looking for a Counsel, Commercial to join our growing Legal team, reporting to Snorkel’s Associate General Counsel, Commercial. This is a key role across Snorkel’s commercial contracting function, including vendor agreements and customer agreements. You will serve as a trusted legal partner to business teams across the company, drafting, reviewing, and negotiating a wide range of commercial contracts while helping build scalable processes. You’ll work closely with cross-functional stakeholders, combining strong commercial legal skills with the hands-on, execution-oriented approach required in a fast-growing technology company. This hybrid role is based in San Francisco or New York City. Responsibilities Draft, review, and negotiate a broad range of commercial contracts, including vendor and customer agreements, NDAs, MSAs, SOWs, order forms, and other commercial arrangements. Serve as a trusted legal partner to cross-functional teams on commercial contracts. Manage a high volume of contracts and competing priorities, ensuring timely execution and alignment with business objectives. Review and negotiate commercial

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! The Role We're looking for our founding AI Data Product Manager to own Snorkel's Agentic Data and RL Environments roadmap. In this role, you'll lead the product strategy for a variety of data types (e.g. Agentic Coding, Computer Use). You will shape the roadmap for the datasets Snorkel invests in by understanding the market, incorporating frontier lab needs and collaborating with researchers at Snorkel and our academic partners. This role is highly cross-functional, sitting between Research, GTM and Operations. As a founding member for this role, you will be in charge of setting up the frameworks to build the roadmap, gather data from relevant sources, and share the roadmap with both internal and external stakeholders. What You'll Do Own the "data as a product" roadmap for Snorkel's Agentic and RL Environment focus areas, working x-functionally with research, academic partners, and GTM to define the skills and capabilities for our datasets Shape new "data" product areas and work with academic partners and research leaders to build Snorkel's competitive edge in the market Collaborate cross-functionally to help shape the roadmap and data strategy and influence bu

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 This Role We're looking for a Staff HR Business Partner to build and own the people strategy for Snorkel's Data as a Service (DaaS) organization. This role is hybrid ( 3 days/week in office) in San Francisco, CA . The DaaS org is a delivery-first team that has more than tripled in size over the last six months, with no signs of slowing. They deliver high-quality data operations and AI deployment outcomes for frontier labs and AI teams. This org has a unique composition: forward deployed engineers, technical and operations delivery managers, a supply team managing a workforce comprised of multiple worker types at scale, and others. The people challenges here require an HRBP who has seen this kind of complexity before, such as workforce planning across FTEs and contractors, building a high performance culture rooted in delivery outcomes, and keeping a geographically dispersed, operationally complex team connected to Snorkel's culture. You'll partner directly with our DaaS GM and leadership team, and you'll need to be as comfortable in the operational weeds as you are in strategic conversations. The ideal background is professional services, managed services

At Scale, we develop reliable AI systems for the world’s most important decisions. Scale’s product marketing team is responsible for developing and executing strategies that drive awareness and engagement for Scale’s offerings amongst our core audiences. We take a data-driven approach to understand our customers’ needs and challenges, ensuring that their voices are reflected in product development and messaging. We partner closely with product, engineering, research, sales, comms, and the broader marketing team to create a cohesive customer experience across all our channels. We aim to provide valuable insights and resources that help our customers execute on their AI transformation journey. This role will focus on developing and optimizing vertical-specific messaging and content for Scale’s applications business to ensure our messaging resonates with core buyers across verticals. The ideal candidate combines strategic thinking with hands-on execution. You will: Develop clear, compelling messaging for enterprise offerings tailored to key personas within target verticals Create marketing assets, including slide decks, videos, blog posts, and one-pagers, that effectively communicate our value propositions to vertical leaders and support our sales team’s pursuits Lead positioning and sales enablement efforts to drive awareness and engagement for Scale’s offerings. Drive cross-functional marketing programs around target verticals, in conjunction with product, engineering, sales, and growth marketing to create a cohesive customer experience and contribute to pipeline targets Collaborate with field marketing and events teams to develop vertical-specific event strategies, content, and experiences that drive engagement within customer and target accounts Drive customer marketing efforts, creating both strategy and tactics to maximize the value Scale and customers get from our shared success, including case studies, testimonials, visual assets and event particip