Research Engineer, QC Automation

About the Role

This is the top hiring priority on a ~15-person engineering team building infrastructure for reinforcement learning environments and post-training AI datasets. As a Research Engineer focused on QC Automation, you'll own the systems that ensure training data quality scales with growing demand — a critical function that sits at the intersection of engineering rigor and research judgment.

What You'll Do

• Automate quality control for training data produced by companies using the platform's infrastructure.

• Build QC systems grounded in genuine human understanding and judgment, rather than heavy LLM reliance.

• Define and enforce quality standards for AI training data end-to-end.

• Design experiments and metrics to grade agent outputs across diverse tasks.

• Partner with data vendors to debug quality issues, diagnose agent failure modes, and improve their data generation processes.

• Translate QC learnings into auditing systems, including sampling strategies and rule-based or model-assisted validation pipelines.

• Continuously integrate QC insights into infrastructure tools and the vendor portal to reduce anomalies and edge cases.

What We're Looking For

• 2–4 years of experience in engineering or research roles, ideally focused on QC automation or data quality.

• 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.

• Demonstrated ability to create QC systems based on human judgment rather than defaulting to LLM-based approaches.

• Experience designing experiments and metrics to grade agent outputs, and partnering with data vendors to provide actionable feedback.

• Solid knowledge of statistics and comfort designing metrics and QA/QC processes.

• Strong written and verbal communication skills for effective cross-timezone collaboration.

• Genuine curiosity, intellectual range, and the ability to work autonomously in fast-paced, early-stage environments.

Compensation & Benefits

Salary range: $150,000 – $250,000 USD annually. Visa sponsorship is available for qualifying candidates.

Location

On-site in San Francisco, CA for U.S.-based candidates; on-site in Singapore for Southeast Asia–based candidates. Fully remote independent contractor arrangements are also considered for candidates based elsewhere, particularly in Europe.