Member of Technical Staff - Data Quality Engineer Post-training

You will define and operationalize measurable data-quality standards for LLM post-training and evaluation. You will analyze datasets, build and validate automated QA methods, create reusable quality pipelines, provide feedback to vendors, and monitor quality trends to improve acceptance criteria.

Responsibilities

• Own upstream data quality for LLM post-training and evaluation
• Translate requirements into measurable quality signals
• Provide actionable feedback to external data vendors
• Design, validate, and scale automated QA methods
• Build reusable QA pipelines for model training and evaluation
• Monitor and report data quality over time
• Improve quality standards, processes, and acceptance criteria

Requirements

• Experience building data pipelines, QA systems, or evaluation workflows for post-training data and agentic environments
• Understanding of SFT, RL, training, and evaluation
• Experience designing automated quality checks
• Proficiency in Python
• Experience building ML or LLM workflows
• Experience with large datasets and automated evaluation or quality-checking systems
• Familiarity with LLM training and evaluation
• Communication skills

Benefits

• Stock options
• Medical, dental, vision, and life insurance
• Annual wellness allowance
• Daily office lunch and dinner
• 22 weeks of paid parental leave
• Unlimited paid time off in the U.S.
• 30 vacation days in the U.K.
• Visa sponsorship support
• Regular off-sites, happy hours, and team celebrations