Research Engineer, Synthetic Data
At a glance
Mid-level AI Research role at HUD. San Francisco · full-time · $100,000–$230,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Turn expert workflows from professional and technical fields into training tasks for AI agents
- Create generation approaches that make synthetic tasks varied, realistic and useful for learning
- Build tools that change, check and refine synthetic tasks
- Study agent results on these tasks to see what they teach and where they break down
- Create measures for task variety, realism and learnability
What you bring
- You can work proficiently with Python, Docker and Linux
- You have researched synthetic data and can explain your methods and its limitations
- You have built synthetic data pipelines from start to finish without a fully mapped plan
- You have worked with environments, evaluations or benchmarks
Who this fits
This role suits an engineer who can reason carefully about task design, scoring and failure cases, and work through open-ended problems. The position is full-time and offers San Francisco or Singapore offices, or remote work with substantial overlap with either time zone. Relocation and visa support is available for strong full-time candidates moving to the US or Singapore.
From the employer
About HUD
HUD's mission is to build reliable, fair and open infrastructure for AI data. We want data to be valuable for the people who create it and trustworthy for the labs that train on it. Our team is a quickly growing group of researchers, engineers and operators building the economy that shapes what AI will become. Backed by $16M from top VCs and YC (W25), our marketplace and platform are used by startups, Fortune 500 companies and frontier labs.
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), the former #1 ranked Catan player in the world, 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 (US and Singapore employees)
Lunch and dinner for 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) and a health/wellness stipend (Singapore 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.
Two top-floor offices in San Francisco’s Union Square and Singapore’s Raffles Place
Annual travel budget to visit either office
Compensation
Actual offers are adjusted for experience and location, but our base salary bands are
San Francisco (and other major US cities): $135,000 - $230,000
Singapore: $100,000 - $175,000
Rest of world: $100,000 - $175,000
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!