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 automate QC for training data created by companies using HUD’s infrastructure. You’ll build the systems that scale quality to help us meet our continued strong demand.

Responsibilities

Create QC systems based on true understanding and human judgement, without relying heavily on LLMs

Define and enforce quality standards for training data

Design experiments and metrics to grade agent outputs

Partner with data vendors to debug quality issues and diagnose agent failure modes, provide actionable feedback, and improve their data generation processes

Translate QC learnings into systems for auditing supplier-generated datasets, including sampling strategies, validation pipelines (rule-based and model-assisted), and feedback loops

Continuously integrate QC learnings into infrastructure tools and data vendor portal to reduce anomalies, inconsistencies, and edge cases

Experience

You may be a good fit if you have

Proficiency in Python, Docker, and Linux environments

Strong understanding of what “good data” means and how to measure it

Genuine curiosity of different domains and great at asking questions to understand them

Built scalable data validation pipelines and automated QA/QC systems end-to-end without a fully prescribed roadmap

Experience working on benchmarks and evals - you can reason about what makes a task realistic, a rubric reliable, an environment usable, and a trajectory useful for RL training

Early-stage startup experience with ability to work independently in fast-paced environments

Strong candidates may also

Have knowledge of statistics

Have strong written and verbal communication skills for collaboration with our partners and team members across time zones

Be comfortable designing metrics, experiments, and QA/QC processes, not just executing them

Have experience with existing benchmarks and can reason about how to construct tasks in new evals

Thrive in unstructured problem spaces

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)