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San Francisco, California, United States
Hybrid
Available
HUD'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.
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.
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
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 Size: ~25 people currently, mostly full-time in-person, but some remote.
Our team: Our team brings together five International Olympiad medalists across IOI, ILO and IPhO, researchers published at NeurIPS and ICLR, and engineers and researchers from Google DeepMind, Amazon, AWS, Meta, Qwen, GLM, and Mercor. It also includes operators from BCG and Uber, the first security hire at one of the largest crypto exchanges, serial AI startup founders, former quant researchers, artists and the former #1 ranked Catan player in the world.
Company stage: We have 8 figures in funding and are scaling profitably and quickly to meet very strong demand.
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.
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
401k with a 4% match
Other perks including an Equinox membership 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
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!