Research Engineer, Synthetic Data
At HUD · San Francisco; Singapore; Remote (Asia); Remote (North America); San Francisco, California, United States
Salary: US$100,000–230,000 a year
- Engineering
- Full-time
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Where you can work from
Open to Singapore and the United States
“Remote (Asia)”
From the location.
“Remote (North America)”
From the location.
“San Francisco”
From the location.
“Singapore”
From the location.
“San Francisco, California, United States”
From the job board field.
“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.”
From the job description.
Working hours
Asian hours
“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.”
Relocation
Relocation help
“Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US or Singapore.”
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- Posted
- 13 July 2026
- First seen by us
- 3 November 2026
- Last checked
- 5 hours ago
Job description
From HUD’s job post, as they wrote it.
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.
Read the full description
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 brings together five International Olympiad medalists across IOI, ILO and IPhO, researchers published at NeurIPS and ICLR, and engineers and researchers from Google DeepMind, Amazon, AWS, Meta, Qwen, GLM, and Mercor. It also includes operators from BCG and Uber, the first security hire at one of the largest crypto exchanges, serial AI startup founders, former quant researchers, artists and the former #1 ranked Catan player in the world.
* 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
* 401k with a 4% match
* Other perks including an Equinox membership 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 [email removed] or elsewhere if we missed your application!
Research Engineer, Synthetic DataHUD
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