Lead Research Engineer, Data Quality
About the Role
Lead the data quality team at an early-stage AI evaluation company, building the strategy and systems used to assess and improve training data for AI agents. Your work will help ensure data is realistic, reliable, and useful for training.
What You'll Do
Lead development of systems to evaluate tasks across reinforcement learning environments, synthetic data, benchmarks, and domain-specific workflows.
Define quality standards, metrics, experiments, and processes for assessing agent outputs.
Develop scalable synthetic data validation methods, including failure analysis, task mutation checks, and trajectory audits.
Partner with research engineers, domain experts, and data vendors to diagnose issues and improve data generation workflows.
Turn research insights into production tools, dashboards, validation pipelines, and feedback loops.
Mentor research engineers and promote technical rigor and clear communication.
What We're Looking For
At least 5 years of research or engineering experience building AI or machine learning data evaluation and quality systems.
