--- title: 'Senior Research Manager at HUD' canonical: 'https://feeny.ai/job/senior-research-manager-hud-san-francisco-cgem51kng9yw' type: 'job' last_seen: '2026-10-13' --- # Senior Research Manager at HUD - **Company:** HUD - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-09-26 - **Last confirmed live:** 2026-10-13 - **Apply:** https://jobs.ashbyhq.com/hud/7b78d641-69cc-4c5a-8cd7-276c7229eedd ## Job description ## About HUD [HUD](https://www.hud.ai/)'s mission is to build reliable, fair and open infrastructure for AI data. We want data to be valuable for the people who create it and trustworthy for the labs that train on it. Our team is a quickly growing group of researchers, engineers and operators building the economy that shapes what AI will become. Backed by $16M from top VCs and YC (W25), our marketplace and platform are used by startups, Fortune 500 companies and frontier labs. ## About the role We’re looking for a Research Manager to lead research that makes HUD’s agent training data and evals more useful for improving frontier models. You’ll lead research engineers through ambiguous projects, and turn findings into methods that can be used at scale. You’ll stay close to the technical work while helping the team choose the right questions, run rigorous experiments, and deliver results. This role calls for an understanding of how and why models train: which signals teach useful behavior, where apparent progress is misleading, and how data and eval design can change outcomes. ## Responsibilities - Set the research direction for data quality, including how HUD measures how training data impacts agent behavior and performance after training, and what makes data valuable - Lead synthetic data efforts to understand how various data types can be efficiently transformed into formats useful for training - Lead research engineers from problem definition through experiments, implementation, and clear conclusions; coach them to strengthen technical judgment and execution - Design and review experiments that connect model behavior and failure modes to data, environment, and reward design - Develop methods for validating and improving training data at scale, including trajectory audits, adversarial checks, and feedback loops that help users improve their data - Partner with research engineers, domain experts, and data vendors to turn research insights into better workflows, tools, and quality standards - Communicate findings and tradeoffs clearly so the team can prioritize work and apply what it learns across research areas ## Experience You may be a good fit if you have: - Experience leading technical research projects to completion, from an open question to evidence, a decision, and a working result - Experience directly managing and mentoring researchers or research engineers while remaining engaged in technical work - A strong understanding of machine learning and reinforcement learning, including how training objectives, data, and feedback shape model behavior - Experience with agent training data, evals, benchmarks, synthetic data, or model evaluation infrastructure - Sound experimental judgment: you can distinguish a useful training signal from a task or metric that only looks convincing - Strong written communication and the ability to explain methods and findings to researchers, engineers, and external partners Strong candidates may also have: - Built scalable data quality systems or validation pipelines for model training - Experience diagnosing reward hacking, grader errors, or other subtle agent failure modes - Experience translating research findings into tools and processes used by others - Early-stage startup experience and strong communication skills for collaboration across teams and time zones We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria. ## Team & company details - Team Size: ~25 people currently, mostly full-time in-person, but some remote. - Our team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc. - Company stage: We have 8 figures in funding and are scaling profitably and quickly to meet very strong demand. Logistics - Employment: Full-time. - Location: We have offices in San Francisco or Singapore but are open to remote candidates who can work hours that 70-80% overlap with either San Francisco or Singapore time zones. - Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US or Singapore. - Timeline: Applications are rolling. The process is 2 technical interviews and a 2-3 day work trial. ## What we offer - Competitive compensation - 100% covered top-of-the-line medical, dental, and vision (US and Singapore employees) - Lunch and dinner for in-office employees - Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays - Other perks including an Equinox membership, 401k, and commuter benefits (US employees) and a health/wellness stipend (Singapore employees) - Unlimited* access to tokens for ChatGPT, Claude Code, Cursor, etc. *By unlimited, we mean no one on our token usage leaderboard has ever hit a limit. So we have no idea what the limit is. - Two top-floor offices in San Francisco’s Union Square and Singapore’s Raffles Place - Annual travel budget to visit either office ## Compensation Actual offers are adjusted for experience and location, but our base salary bands are - San Francisco (and other major US cities): $200,000 - $295,000 - Singapore: $150,000 - $225,000 - Rest of world: $120,000 - $225,000 Due to high volume, we may not actively respond to every application, but feel free to contact us at recruiting@hud.so or elsewhere if we missed your application! ## About HUD ## Company Overview - **One-liner**: HUD (Human Union Data, Inc.) provides the first comprehensive evaluation platform for Computer Use Agents (CUAs), enabling frontier AI labs to build reinforcement learning environments and run detailed evals for AI agents that browse the web. - **Entity Type**: Private (YC W25 startup; raised $500K in Pre-Seed funding led by Y Combinator) - **Headquarters**: San Francisco, California, United States - **Founded**: 2025 - **Founders**: Jay Ram (CEO), Parth Patel (CTO) ## Core Business - **Primary industry**: AI infrastructure – evaluation and reinforcement learning environments for browser‑based AI agents. - **Target customers**: Frontier AI labs (B2B), researchers building computer‑use and browser‑use agents. - **Mission / Purpose**: Provide the infrastructure to make AI agents work reliably in the real world by enabling detailed evals across thousands of tasks. ## Products & Services - **[CUA Evals Platform](https://www.hud.so/)**: An all‑in‑one platform for evaluating computer‑use and browser‑use AI agents. Supports 40+ models (GPT, Kimi, Qwen, etc.) and includes hundreds of environments and thousands of tasks. Used to generate both evaluation results and training data for reinforcement learning. ## Market Standing - **Valuation**: $3.3M (most recently disclosed, per Latka, Sep 2025) - **Key Metric**: $1.1M revenue (2025) – note: Latka reports the company as bootstrapped, but other sources (YC, LinkedIn) show $500K in outside funding; this may reflect different accounting or a conflict in data. - **Total Funding**: $500,000 (Pre-Seed, led by Y Combinator, with participation from several angel investors) - **Notable Investors / Partners**: Y Combinator (lead), backed by YC W25 batch; works closely with frontier AI labs. - **Growth Signals**: - Headcount grew ~150% YoY (from ~4 to ~9–15 employees). - Launched public beta in March 2026. - Active job postings increased 66.7% month‑over‑month. - Strong social engagement: LinkedIn followers grew 448.9% yearly. ## Competitive Advantages - First‑mover in a nascent category: HUD’s platform is described as the first comprehensive evaluation tool specifically for Computer Use Agents. - Tight integration with Y Combinator and frontier AI labs provides direct feedback and early‑adopter relationships. - Supports a wide range of models (40+) and can generate RL training data, not just eval results. ## Strategic Focus - Scale the platform to serve more frontier labs and researchers. - Expand the number of environments and tasks covered by evaluations. - Continue building out reinforcement learning infrastructure for agentic AI. ## Why Work Here - **Culture**: Small, ambitious team (≈15 people) backed by Y Combinator, focused on solving a cutting‑edge problem in AI reliability. - **Work Policy**: In‑office / in‑person in San Francisco (HQ). Some roles listed as hybrid. - **Notable Perks**: - Competitive salary ranges (e.g., Platform Engineer: $140K – $250K; other roles $70K – $120K). - Opportunity to shape the infrastructure that leading AI labs depend on. - Fast‑paced startup environment with high ownership. ## Sources 1. [Y Combinator – HUD](https://www.ycombinator.com/companies/hud) 2. [LinkedIn – HUD](https://www.linkedin.com/company/hud-evals) 3. [Built In San Francisco – HUD](https://www.builtinsf.com/company/hud) 4. [Latka – HUD](https://getlatka.com/companies/www.hud.so) 5. [Hud Careers Page](https://jobs.ashbyhq.com/hud) ## Other roles at HUD - [Technical Writer](https://feeny.ai/job/technical-writer-hud-san-francisco-mxvv41mr9nqd) — San Francisco, CA - [Research Engineer, Robotics Evals](https://feeny.ai/job/research-engineer-robotics-evals-hud-san-francisco-tp487dh7xgd3) — San Francisco, CA - [Customer Operations Lead](https://feeny.ai/job/customer-operations-lead-hud-san-francisco-jvc21gxyfjnn) — San Francisco, CA - [Product Engineer](https://feeny.ai/job/product-engineer-hud-san-francisco-jby01j7qaewq) — San Francisco, CA - [Software Engineer, Data Quality](https://feeny.ai/job/software-engineer-data-quality-hud-san-francisco-8sbd33btzf00) — San Francisco, CA - [Research Engineer, Robotics Data](https://feeny.ai/job/research-engineer-robotics-data-hud-san-francisco-j795v7ty1k1n) — San Francisco, CA - [Full-Stack Software Engineer, Design](https://feeny.ai/job/full-stack-software-engineer-design-hud-san-francisco-vs5wencbfdpw) — San Francisco, CA - [Product Manager, Platform](https://feeny.ai/job/product-manager-platform-hud-san-francisco-3yfpfb6vb89p) — San Francisco, CA - [Product Manager, Marketplace](https://feeny.ai/job/product-manager-marketplace-hud-san-francisco-ejv2xetasazj) — San Francisco, CA - [Business Operations](https://feeny.ai/job/business-operations-hud-san-francisco-32pxcg3t5mbs) — San Francisco, CA