Overview
Research Engineer, QC Automation Jobs in San Francisco, CA at Clera
About the Role
An early-stage AI infrastructure company is hiring a Research Engineer, QC Automation — the #1 priority hire on the engineering team right now. You’ll own end-to-end automation of quality control for AI training data generated by companies using the platform’s infrastructure. This is a high-impact, high-autonomy role sitting at the intersection of data engineering, research, and systems design.
You’ll be joining a ~15-person engineering group composed of Olympiad medalists, AI startup founders, and published researchers, working on one of the most critical challenges in post-training data quality for reinforcement learning.
What You’ll Do
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Automate quality control for training data produced by companies using the platform’s infrastructure.
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Build QC systems grounded in true understanding and human judgment — not heavy reliance on LLMs.
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Define and enforce quality standards for post-training datasets.
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Design experiments and metrics to grade agent outputs.
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Partner with data vendors to debug quality issues, diagnose agent failure modes, and improve data generation processes.
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Translate QC learnings into auditing systems, including sampling strategies and rule-based or model-assisted validation pipelines.
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Continuously integrate QC learnings into infrastructure tooling and the data vendor portal to reduce anomalies, inconsistencies, and edge cases.
What We’re Looking For
Required:
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2–4 years of experience in engineering or research roles.
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Proficiency in Python, Docker, and Linux environments.
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Strong understanding of what “good data” means and how to measure it.
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Proven experience building scalable data validation pipelines and automated QA/QC systems end-to-end.
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Experience working on benchmarks and evals — including reasoning about realistic tasks, reliable rubrics, and useful trajectories for RL training.
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Knowledge of statistics and comfort designing metrics, experiments, and QA/QC processes.
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Strong written and verbal communication skills for collaborating across time zones.
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Genuine curiosity across domains and an ability to ask questions that drive understanding.
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Ability to thrive in unstructured problem spaces and work independently in a fast-paced, early-stage startup environment.
Nice to have:
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Background in AI evaluation, reinforcement learning environments, or post-training data pipelines.
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Experience with reward signal analysis or reward hacking detection.
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Prior startup experience or demonstrated comfort with ambiguity and self-direction.
Compensation & Benefits
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Salary: $150,000 – $250,000 USD annually -
Visa sponsorship available for eligible candidates
Location
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San Francisco, CA (on-site) for U.S.-based candidates -
Singapore (on-site) for Southeast Asia–based candidates -
Fully remote as an independent contractor for candidates based elsewhere, particularly in Europe
Title: Research Engineer, QC Automation
Company: Clera
Location: San Francisco, CA
Category:
