Research Manager

HUD - 4.2

San Francisco, CA Job Details Full-time 19 hours ago Benefits Commuter assistance Paid holidays Health insurance Dental insurance 401(k) Paid time off Vision insurance Qualifications AI models Data integrity assurance Research design Technical writing for researchers Reinforcement learning Management Data validation techniques Startup experience Coaching Design of experiments Process design Scalable systems Managing data teams Research project design Collaborative research Research project technical leadership Machine intelligence Managing engineering teams Task prioritization Data quality monitoring Engineering research Mentoring Developing data pipelines Scalability Managing projects Model training Technical training Machine learning (ML) fundamentals Benchmarking Senior level Full Job Description About HUD HUD is building infrastructure to create RL training data and evals for frontier AI agents, as well as a marketplace to sell these to frontier labs through the HUD marketplace. Our platform is used by frontier labs, Fortune 500 companies, and startups. We've raised $16M from top VCs and were YC W25. 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 whether tasks, trajectories, rewards, and evals are reliable and useful for training agents 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, grader checks, and feedback loops 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 from Blue Shield of CA (US employees) Lunch and dinner when you're in the office (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) 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. Due to high volume, we may not actively respond to every application, but feel free to contact us at or elsewhere if we missed your application!