Build high-quality benchmarks for evaluating frontier AI agents on domain-specific tasks. Own design, implementation, and quality of internal agent benchmarks while collaborating with subject-matter experts. Requires strong Python skills and experience with model evaluation environments.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
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 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
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
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- 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
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.
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- 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.
- 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.
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