Lead Research Engineer, Data Quality
hudAI Agent company
San Francisco, United StatesLead
Y Combinator
Liquid 2 Ventures
Standard Capital
Exceptional Capital
Twenty Two Ventures
Dylan Patel
Data & AI
About the role
TL;DR
Lead the data quality strategy and systems for frontier AI agent training data.
- •HUD is building infrastructure for RL training data and a marketplace for frontier AI agents.
- •We are seeking a Lead Research Engineer, Data Quality to own the strategy and systems for measuring, improving, and scaling the quality of training data for frontier agents.
- •Key Responsibilities Lead HUD’s data quality strategy including building QC systems and designing experiments to grade agent outputs.
- •Develop new methods for validating synthetic data at scale.
- •Partner with research engineers and domain experts to diagnose quality issues and improve data generation workflows.
- •Turn qualitative research insights into production systems, internal tools, dashboards, and validation pipelines.
- •Requirements Advanced proficiency in Python, Docker, and Linux environments.
- •Deep intuition for data quality and experience building QC systems, evals, or synthetic data pipelines.
- •Comfort working across messy human and technical systems.
- •Strong written communication skills.
Required skills
PythonDockerLinuxGitOpenAI APIAnthropic API
Nice-to-have skills
Mentoring
Domain expertise
aideveloper-tools
Benefits & perks
Competitive compensation, 100% covered top-of-the-line medical, dental, and vision, Lunch and dinner when you’re in the office, Company-wide holiday break, PTO, Paid holidays, Equinox membership, 401k, Commuter benefits, Unlimited access to tokens for ChatGPT, Claude Code, Cursor, etc.
Tech stack
PythonDockerLinuxGitOpenAI APIAnthropic API