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 : ~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 email removed] or elsewhere if we missed your application!