Research Engineer, QC Automation

About this role

Join an early-stage AI infrastructure company as a Research Engineer to build and own automated quality control systems for reinforcement learning training data. You'll design scalable QC pipelines, define quality standards, evaluate agent outputs, and partner with data vendors to improve data generation processes in a small, high-caliber engineering team.

What you'll do

• Automate QC for training data produced on the platform's RL infrastructure
• Build QC systems grounded in human judgment and first-principles understanding rather than heavy LLM reliance
• Define and enforce quality standards for post-training datasets
• Design experiments and metrics to evaluate and grade agent outputs
• Partner with data vendors to debug quality issues and improve data generation processes
• Develop auditing systems including sampling strategies and validation pipelines

What they're looking for

• Python programming
• Docker and containerization
• Linux environments
• Data validation and QA/QC pipeline design
• Reinforcement learning benchmarks and evaluation
• Training data quality measurement and standards definition
• Experimental design and metrics development
• Statistical analysis and measurement frameworks

Benefits

• Salary: $150,000–$250,000 USD annually
• Equity participation in early-stage AI infrastructure company
• Visa sponsorship available
• On-site roles in San Francisco or Singapore, or remote contractor options
• Work with Olympiad medalists, AI founders, and published researchers
• High autonomy in unstructured problem spaces