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 Research Engineers to build high-quality benchmarks for evaluating frontier agents on domain-specific tasks. You’ll build benchmarks that are technically rigorous, practically useful, and credible to frontier labs.
Responsibilities
Own the design, implementation, and quality of HUD’s internal agent benchmarks
Work with subject-matter experts to define tasks and create domain-specific benchmarks that evaluate agents on realistic workflows
Build infrastructure to reliably run models and agents against benchmark tasks
Develop metrics and analyses to understand benchmark difficulty, reliability, and failure modes
Validate whether benchmark performance correlates with real-world evals, customer needs, and lab expectations
Write clear documentation and benchmark reports that make results legible and credible to technical audiences
Experience
You may be a good fit if you have:
Proficiency in Python, Docker, and Linux environments
Published papers or written technical blogs on relevant topics such as public benchmarks and their limitations, model failure modes, etc. - please link in your application
Strong understanding of what a “good benchmark” means and what makes one realistic, reliable, and useful
Experience working on environments and evals
Curiosity and ability to truly understand how workflows in various domains work
Strong candidates may also:
Be detail-oriented and able to spot subtle inconsistencies or edge cases in tasks
Be able to reason from first principles about task design, scoring, and failure modes
Thrive in unstructured problem spaces
Early-stage startup experience with ability to work independently in fast-paced environments
Strong communication skills for remote collaboration across 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: ~15 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 high revenue growth. We’re scaling profitably and quickly to meet very strong demand.
Logistics
Employment: Full-time.
Location: On-site only, for now. You can join the team in the San Francisco Bay Area or Singapore offices.
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
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 recruiting@hud.so or elsewhere if we missed your application!