Research Engineer, QC Automation
Core
Build systems to automate quality control (QC) for training data used in Reinforcement Learning (RL) training for frontier AI agents.
Role type
Research Engineer (QC Automation)
Builds
Scalable data validation pipelines, automated QA/QC systems, and infrastructure tools for auditing supplier-generated datasets.
Domain
Artificial Intelligence / Reinforcement Learning / Data Infrastructure
Deliverable
production ML models | infrastructure
Required skills
Python, Docker, Linux, scalable data validation pipelines, automated QA/QC systems, benchmarks and evals design, statistics, domain curiosity
Preferred skills
statistics, metrics design, experiment design, unstructured problem solving
Technologies
Python, Docker, Linux
Responsibilities
Create QC systems based on human judgement without relying heavily on LLMs; Define and enforce quality standards for training data; Design experiments and metrics to grade agent outputs; Partner with data vendors to debug quality issues and improve data generation processes; Translate QC learnings into systems for auditing supplier-generated datasets; Continuously integrate QC learnings into infrastructure tools and data vendor portal.
Seniority
Individual Contributor (IC), early-stage startup environment
