Research Engineer, Synthetic Data
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 our synthetic data pipeline. You’ll turn domain-specific workflows into synthetic training tasks that are realistic enough to enough to teach useful behavior, structured enough to generate at scale, and difficult enough to expand model capabilities.
Responsibilities
Work with subject-matter experts to create synthetic tasks for training AI agents across a range of professional and technical domains
Design synthetic task generation methods that produce diverse, realistic, and learnable tasks
Build systems and tooling to mutate, validate, and improve synthetic tasks
Analyze model and agent performance on synthetic tasks to understand what the tasks are teaching and where they fail
Develop metrics to quantify and understand synthetic task diversity, realism, learnability, etc.
Experience
You may be a good fit if you have:
Proficiency in Python, Docker, and Linux environments
Have experience with synthetic data research methods - please elaborate in your application
Strong understanding of what “good synthetic data” means and its limitations
Built synthetic data pipelines end-to-end without a fully prescribed roadmap
Experience working on environments, evals, and benchmarks
Strong candidates may also:
Be detail-oriented and able to spot subtle inconsistencies or edge cases in synthetic data
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!
Check your CV against this role
Drop your CV. You get a 0-100 fit score against the actual job description, plus the read a senior engineering lead would write. Private to you.
Score this once, or every future role
Start the candidate journey and every new role on the board gets scored against you.
Five minutes. Tell us what you’re after, drop your CV once, pick how we should reach out. You get a candid read back and you only hear from us when a role fits.