Research Engineer, Synthetic Data

About hud

Platform for building RL environments and evals

Tech description:

AWS
Docker
Rust
Postgres
Python
Next + React

Job description:

# **About HUD**

[HUD](https://www.hud.ai/) 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 [[email removed]](mailto:[email removed]) or elsewhere if we missed your application!