Lead Research Engineer, Data Quality
Core
Lead the strategy and systems for measuring, improving, and scaling the quality of training data for frontier AI agents.
Role type
Lead Research Engineer, Data Quality
Builds
QC systems, evals, benchmarks, synthetic data pipelines, validation workflows, and internal research tools
Domain
Frontier AI, Reinforcement Learning, Data Infrastructure
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Python, Docker, Linux, data quality reasoning, building QC systems, designing experiments, building validation pipelines
Preferred skills
leading teams on ambiguous technical projects, working with subject-matter experts, designing metrics and QA/QC processes, early-stage startup experience
Technologies
Python, Docker, Linux
Responsibilities
Lead data quality strategy including building QC systems and defining quality standards; Develop new methods for validating synthetic data at scale; Partner with research engineers and domain experts to diagnose quality issues; Turn qualitative research insights into production systems and validation pipelines; Mentor research engineers to maintain technical rigor
Seniority
Lead, hands-on IC with mentorship
