Lead Research Engineer, Data Quality — Scale Training Data

PVH (Tommy Hilfiger/Calvin Klein); San Francisco (CA); Hybrid; USD 190,000 - 280,000; Full time

Benefits offered by this job

Medical, dental, vision (100% covered)

Lunch and dinner in the office

Equinox membership

401k

Commuter benefits

Relocation and visa sponsorship

Job summary

HUD is seeking a Lead Research Engineer, Data Quality to elevate the quality of training data for frontier AI agents. You will spearhead QC systems, evaluate thousands of tasks across RL environments, synthetic data, benchmarks, and specialized workflows.

You will mentor engineers, build production-grade validation pipelines, and partner with researchers, domain experts, and vendors to diagnose issues and scale data generation.

Qualifications

• Experience leading data-quality initiatives and teams.
• Ability to translate qualitative research into production-grade pipelines.
• Strong written and verbal communication to researchers, engineers, and external audiences.
• Comfort working with messy data, domain experts, and vendors.

Responsibilities

• Lead HUD's data quality strategy including QC systems and quality standards.
• Develop scalable validation for synthetic data, audits, and benchmarks.
• Collaborate with researchers, domain experts, and data vendors to fix quality issues.
• Translate research insights into production systems, dashboards, and validation pipelines.
• Mentor engineers to maintain rigor, clarity, and speed.

Skills

Leadership

Communication

Research mindset

Tools

Python

Docker

Linux

Job description

HUD is seeking a Lead Research Engineer, Data Quality to elevate the quality of training data for frontier AI agents. You will spearhead QC systems, evaluate thousands of tasks across RL environments, synthetic data, benchmarks, and specialized workflows.

You will mentor engineers, build production-grade validation pipelines, and partner with researchers, domain experts, and vendors to diagnose issues and scale data generation.