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 an Applied Research Engineer to own implementation. Our data buyers and sellers often have time-sensitive asks such as troubleshooting and running evals or cleaning data at scale. You’ll take the lead on diagnosing ambiguous technical problems and resolving them. This work is broad and hands-on - the right fit is a strong generalist AI engineer who can move quickly and wants to work closely with frontier AI labs and data vendors.
Responsibilities
Own technical deployment requests from frontier AI labs, data vendors, and internal teams from triage to completion
Ask the right questions to clarify ambiguous asks and identify what actually needs to be done
Build tools and one-off pipelines to solve urgent customer or partner problems
Coordinate with research and GTM teams to unblock deployments
Balance speed and quality in situations where customers need fast turnaround and the path is not fully specified
Document recurring issues and turn repeated manual work into reusable tools or processes
Experience
You may be a good fit if you have:
Proficiency in Python, Docker, and Linux environments
Experience working on benchmarks and evals - you can reason about what makes a task realistic, a rubric reliable, an environment usable, and a trajectory useful for RL training
Strong debugging instincts across code, data, and environments
Demonstrated ability to operate independently in ambiguous situations without a fully prescribed roadmap
Strong judgment about when to move fast, when to escalate, and when correctness or security requires extra care
Comfort working directly with technical customers, vendors, or cross-functional internal teams
Strong candidates may also have:
Experience in applied research engineering or forward-deployed engineering
Experience handling urgent production, customer, or deployment issues
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!