Research Engineer, QC Automation

About this role

Research Engineer role focused on building automated quality control systems for reinforcement learning training data. You'll design and implement scalable QC pipelines that combine human judgment with rigorous engineering, working closely with data vendors to maintain data quality at scale.

What you'll do

• Automate quality control systems for RL training data from external vendors using the platform
• Define and enforce quality standards for post-training datasets across the infrastructure
• Design experiments, metrics, and rubrics to evaluate agent outputs and task trajectories
• Partner with data vendors to debug quality issues and improve their data generation processes
• Build sampling strategies and validation pipelines (rule-based and model-assisted) for auditing
• Feed QC insights back into infrastructure tooling and vendor portals to reduce anomalies

What they're looking for

• Python programming
• Docker and containerization
• Linux/Unix environments
• Data validation and QA/QC pipeline design
• Reinforcement learning evaluation and benchmarking
• Statistical design and metrics development
• Human-in-the-loop system design
• Cross-functional communication

Benefits

• Competitive salary: $150,000–$250,000 USD annually
• Visa sponsorship available
• On-site or remote options (SF, Singapore, or Europe)
• Work on cutting-edge AI infrastructure
• Small, focused engineering team (~15 people)
• Ownership of critical QC systems