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

OUR MISSION

Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all.

ABOUT THE ROLE

Data is playing an increasingly crucial role at the frontier of AI innovation. Many of the most meaningful advances in recent years have come not from new architectures, but from better data.

As a member of the Data Team, your mission is to ensure that the data used to train our models meets a high bar for quality, reliability, and downstream impact. You will directly shape how our models perform on critical capabilities.

Working with world-class researchers on our pre-training teams, you’ll help turn fuzzy notions of “good data” into concrete, measurable standards that scale across large data campaigns. We’re looking for engineers who combine strong engineering fundamentals with a deep curiosity about data quality and its impact on model performance.

Working closely with our pre-training teams you will:

- Own upstream data quality for LLM pre-training; as a specialist or generalist across languages and modalities

- Partner closely with research and pre-training teams to translate requirements into measurable quality signals, and provide actionable feedback to external data vendors

- In addition to human-in-the-loop processes, you will design, validate, and scale automated QA methods to reliably measure data quality across large campaigns

- Build reusable QA pipelines that reliably deliver high-quality data to pre-training teams for model training

- Monitor and report on data quality over time, driving continuous iteration on quality standards, processes, and acceptance criteria

ABOUT YOU

- Strong engineering fundamentals with experience building data pipelines, QA systems, or evaluation workflows for pre-training data

- Detail-oriented with ...