Research Engineer, QC Automation
Core
Build quality control systems for training data in reinforcement learning environments to ensure reliable agent evaluations.
Role type
Research Engineer, QC Automation
Builds
Auditing systems, sampling strategies, and rule-based or model-assisted validation pipelines for training data quality.
Domain
AI and reinforcement learning infrastructure
Deliverable
production ML models
Required skills
Python, Docker, Linux, scalable data validation pipelines, end-to-end automated QA/QC systems, reinforcement learning benchmarks and evaluations, training data quality metrics, experiment design, statistics
Preferred skills
None stated
Technologies
Python, Docker, Linux
Responsibilities
Automate quality control for training data generated in reinforcement learning environments; Set and enforce data quality standards using human judgment and clear evidence; Design experiments and metrics to evaluate agent outputs; Work with data vendors to investigate quality issues and improve data generation processes; Turn quality findings into auditing systems; Improve infrastructure tools and vendor portals to reduce anomalies and inconsistencies
Seniority
Mid-level (2-4 years experience)
