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 a Lead Research Engineer, Data Quality to own how HUD measures, improves, and scales the quality of training data for frontier agents. You’ll lead the data quality team in building the systems that evaluate thousands of tasks across RL environments, synthetic data, benchmarks, and domain-specific workflows.

Responsibilities

Lead HUD’s data quality strategy including building QC systems, defining and enforcing quality standards, and designing experiments to grade agent outputs

Develop new methods for validating synthetic data at scale, such as failure-mode analysis, task mutation checks, and trajectory auditing

Partner with research engineers, domain experts, and data vendors to diagnose quality issues and improve data generation workflows

Turn qualitative research insights into production systems, internal tools, dashboards, validation pipelines, and feedback loops

Help build internal research taste around what makes agent training data actually useful, not just superficially correct

Mentor other research engineers to maintain a high bar for technical rigor, clarity, and execution speed

Experience

You may be a good fit if you have

Advanced proficiency in Python, Docker, and Linux environments

Deep intuition for data quality - you can reason about what makes tasks realistic, learnable, diverse, reliable, and useful for training

Experience building QC systems, evals, benchmarks, synthetic data pipelines, validation workflows, or model evaluation infrastructure

Comfort working across messy human and technical systems, including domain experts, vendors, generated data, model outputs, graders, and infrastructure

Strong written communication and the ability to explain methodology clearly to researchers, engineers, labs, and external audiences

Strong candidates may also have

Experience leading teams on ambiguous technical projects from problem definition through implementation and iteration

Experience working with subject-matter experts to capture domain judgment and convert it into scalable review or generation systems

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

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

Be detail-oriented and able to spot subtle inconsistencies or edge cases in data

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