Research Engineer, QC Automation

About the Role This is a top-priority hire for a fast-growing AI infrastructure company building the tooling that powers reinforcement learning environments and post-training data for AI labs. As a Research Engineer focused on QC Automation, you will own the systems that ensure training data quality at scale, sitting within a roughly 15-person engineering team of competitive programming medalists, published researchers, and AI startup founders. What You'll Do - Design and build automated quality control systems for training data produced via the company's infrastructure, grounded in human judgment rather than heavy LLM reliance. - Define and enforce quality standards for RL training data across diverse tasks and environments. - Design experiments and metrics to evaluate and grade agent outputs. - Partner with data vendors to identify and debug quality issues, diagnose agent failure modes, and drive improvements to their data generation workflows. - Translate QC findings into auditing systems, including sampling strategies and rule-based or model-assisted validation pipelines. - Continuously feed QC learnings back into infrastructure tooling and the vendor portal to reduce anomalies, inconsistencies, and edge cases over time. What We're Looking For - 2 to 4 years of experience in engineering or research roles with a focus on QC automation or data quality. - Strong proficiency in Python, Docker, and Linux environments. - Proven track record 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. - Ability to define and measure quality standards for training data using human understanding rather than delegating judgment to LLMs. - Experience designing metrics and experiments to grade agent outputs. - Comfort working with statistics and applying them to QA/QC process design. - Strong written and verbal communication skills for collaborating across time zones. - Genuine curiosity, autonomy, and the ability to thrive in fast-paced, early-stage startup environments with unstructured problem spaces. Compensation & Benefits Salary range: $150,000 to $250,000 USD annually. Visa sponsorship is available. Location On-site in Singapore . Fully remote independent contractor arrangements may also be considered for candidates based outside Singapore, particularly in Europe.