Member of Technical Staff - Data Quality Engineer (Post-training)

Highlights

• Own data quality for LLM post-training shaping agentic tool use and reasoning.
• Build scalable QA pipelines and LLM-as-a-Judge to measure quality at scale.
• Turn fuzzy notions of good data into measurable standards for model training.

What they offer

• Top-tier salary and equity with stock options
• Comprehensive medical, dental, vision, life coverage plus wellness allowance
• Lunch and dinner provided in office daily
• 22 weeks paid parental leave
• Unlimited PTO in U.S. and 30 days in U.K.
• Visa sponsorship and immigration support
• Regular off-sites, happy hours and team celebrations

Ideal candidate

Detail-oriented engineer fascinated by how data quality shapes model behavior, who thrives owning ambiguous problems end-to-end and partnering with researchers to turn quality insights into better models.

Requirements

• Experience building data pipelines, QA systems, or evaluation workflows for post-training data
• Detail-oriented and analytical, able to spot failure modes and subtle data issues
• Understanding of how data quality impacts SFT, RL training and evaluation
• Experience designing and validating automated quality checks including LLM-as-a-Judge
• Comfortable owning problems end-to-end and collaborating with researchers and operations
• Proficiency in Python and building ML/LLM workflows
• Experience with large datasets and automated evaluation systems
• Familiarity with how LLMs are trained and evaluated
• Excellent communication skills across teams