About Snorkel
Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes.
Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!
ABOUT THE ROLE
We're looking for a manager to lead a team of researchers to focus on data evaluation, error analysis and data valuation methods to predict model performance. This team is responsible for showcasing the value and quality of Snorkel’s data for model training and evaluation, understanding where today's frontier models fall short, and turning that understanding into a point of view on what benchmarks and datasets these models will benefit from.
You and your team will be responsible for Snorkel’s data design flywheel by analyzing model failures, finding capability and skill gaps in current models, suggesting the next benchmarks to invest in and then proving the value of this data for our customers.
MAIN RESPONSIBILITIES
- Own a multi-quarter roadmap centered on novel evaluation, error analysis, and data valuation techniques
- Synthesize and share trends from model-failure analysis and benchmarking into recommendations on the datasets the community should focus on and the ones Snorkel should invest in — making this team a primary input to the company's data strategy.
- Focus on data valuation techniques that quantify how Snorkel data meaningfully improves model performance
- Lead and grow a team of researchers, setting a high bar for quality, rigor and speed of execution
- Act as the primary bridge between the team's findings and Product, GTM, and our customers
PREFERRED QUALIFICATIONS
- 7+ years in applied AI, ML, or research roles, with 4+ years managing technical teams.
- A leader who has repeatedly turned research and analysis into business outcomes, and who instinctively connects technical findings to market and customer needs.
- Strong business and market judgment in the AI/ML space — you understand the competitive and frontier-lab landscape and can prioritize accordingly.
- Technically conversant and credible: enough depth in LLM evaluation, benchmarking, and model behavior analysis to set direction, judge experimental quality, and pressure-test results — without needing to be the deepest technical expert in the room.
