Proven track record of translating research into business success
Strong understanding of the AI/ML competitive landscape
Technically knowledgeable in LLM evaluation and model behavior analysis
Exceptional communication and storytelling abilities
Familiarity with data valuation or attribution research is a plus
Responsibilities
Own a multi-quarter roadmap for novel evaluation and analysis techniques
Synthesize model failure trends into actionable dataset recommendations
Focus on data valuation techniques to demonstrate performance improvements
Lead and develop a team of researchers to meet high-quality standards
Act as a bridge between findings and various stakeholders including Product and customers
Benefits
Opportunity to lead and shape a high-impact research team
Engagement in cutting-edge AI/ML projects
Collaboration with a variety of internal and external stakeholders
Support for professional development and growth
Access to advanced technology and resources for research
Full Job Description
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
What We're Looking For
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.
A nose for trends: able to look across many evaluation results and failure cases and extract the signal that should drive what gets built next.
Excellent communication and storytelling skills, with the ability to make technical results legible and persuasive to non-research audiences.
Familiarity with data valuation or data attribution research is a strong plus.
Bonus: experience working with frontier labs, public benchmarks, or commercial AI data/eval products.
About Snorkel AI
Snorkel AI is an artificial intelligence company that provides a platform for building and managing machine learning models. The company was founded in 2019 and is headquartered in San Francisco, California. Snorkel AI's platform is designed to make it easier for developers and data scientists to create and manage machine learning models, using a technique called programmatic labeling. The company's platform is used by a number of large enterprises, including Intel, Google, and Microsoft. Snorkel AI has raised over $50 million in funding to date.
