Research Engineer, QC Automation

ABOUT THE ROLE This is a top-priority role on the Engineering team at an early-stage AI infrastructure company focused on reinforcement learning environments and post-training data. You will own the automation of quality control for training data produced by external data vendors, building systems that scale quality assurance as demand grows. The team is a small, high-calibre group of researchers and engineers working at the frontier of AI alignment. WHAT YOU'LL DO - Automate QC for training data created by companies using the platform's infrastructure. - Build QC systems grounded in human judgment and true understanding, rather than heavy reliance on LLMs. - Define and enforce quality standards for RL training data. - Design experiments and metrics to grade agent outputs. - Partner with data vendors to debug quality issues, diagnose agent failure modes, and improve data generation processes. - Translate QC learnings into auditing systems, including sampling strategies and rule-based or model-assisted validation pipelines. - Continuously integrate QC learnings into infrastructure tools and the vendor portal to reduce anomalies, inconsistencies, and edge cases. WHAT WE'RE LOOKING FOR - 2 to 4 years of experience in research engineering or a similar role focused on QC automation. - Proficiency in Python, Docker, and Linux environments. - Proven experience building scalable data validation pipelines and automated QA/QC systems end-to-end, without a fully prescribed roadmap. - Experience working on benchmarks and evaluations for RL training data, including defining realistic tasks, reliable rubrics, and useful trajectories. - Experience creating QC systems based on human judgment rather than LLM-heavy approaches. - Experience designing experiments and metrics to grade agent outputs. - Experience partnering with data vendors to debug quality issues and provide actionable feedback. - Strong knowledge of statistics and comfort designing metrics and QA/QC processes. - Strong written and verbal communication skills for collaborating across time zones. - Ability to work autonomously and thrive in unstructured, fast-paced early-stage environments. COMPENSATION & BENEFITS Salary range: $150,000 to $250,000 USD annually. Visa sponsorship is available. LOCATION On-site in Singapore. Candidates based in San Francisco or working remotely as an independent contractor, particularly from Europe, may also be considered.