Member of Technical Staff - Data Quality Engineer (Post-training)
Core
Ensure data quality, reliability, and downstream impact for LLM post-training and evaluation datasets used in agentic tool use and reasoning.
Role type
Data Quality Engineer (Post-training)
Builds
Automated QA pipelines, LLM-as-a-Judge frameworks, and measurable quality standards for data campaigns.
Domain
AI/ML, Large Language Models, Post-training
Deliverable
production ML models
Required skills
Python, building data pipelines, designing automated QA systems, LLM-as-a-Judge frameworks, statistical methods, rule-based systems, understanding of SFT and RL training
Preferred skills
Experience with agentic environments, debugging scalable code, translating quality concerns into concrete signals
Technologies
Python, LLM-as-a-Judge, automated evaluation systems
Responsibilities
Own upstream data quality for LLM post-training and evaluation, partner with research teams to translate requirements into measurable quality signals, design and validate automated QA methods, build reusable QA pipelines, monitor and report on data quality over time
Seniority
Mid-level, hands-on IC
