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About the Role:
- This is a top-priority hire on the engineering team at a fast-growing AI infrastructure startup focused on reinforcement learning environments and post-training data.
- As a Research Engineer, QC Automation, you will own the automation of quality control for training data created by companies using the platform.
What You'll Do:
- Automate QC for training data, build systems grounded in human judgment, and define quality standards.
- Design experiments and metrics to grade agent outputs, and partner with data vendors to debug issues.
- Translate QC findings into auditing systems and feed learnings back into infrastructure tools.
What We're Looking For:
- 2-4 years of experience in QC automation or related area, with proficiency in Python, Docker, and Linux.
- Proven track record building scalable data validation pipelines and automated QA/QC systems.
- Experience with RL training data benchmarks, statistics, and working autonomously in fast-paced environments.
AI Infrastructure Startup
The company is a fast-growing AI infrastructure startup focused on reinforcement learning environments and post-training data. With a roughly 15-person engineering team of published researchers and experienced AI practitioners, the culture is fast-paced, unstructured, and research-driven.