Lead Research Engineer, Data Quality
About the Role
Lead the data quality team at an AI and machine learning company focused on reinforcement learning environments and model evaluation. You will shape the systems and research practices that make training data useful for real-world AI agents.
What You'll Do
Lead development of systems that evaluate tasks across reinforcement learning environments, synthetic data, benchmarks, and domain-specific workflows.
Set data quality strategy by establishing standards, building quality control systems, and designing experiments to assess agent outputs.
Develop scalable methods to validate synthetic data, including failure-mode analysis, task mutation checks, and trajectory audits.
Work with research engineers, domain experts, and data vendors to identify quality issues and improve data generation workflows.
Translate research insights into production tools, dashboards, validation pipelines, and feedback loops.
Develop team practices for recognizing training data that is genuinely useful, realistic, and reliable.
Mentor research engineers and uphold strong standards for technical rigor and execution.
