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.