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Director - Research
Director - Research
As a Director on the Research team at Snorkel AI, you will lead a team focused on data-centric research for the next generation of models. This role involves team leadership, collaborating with leading AI labs to define data-centric techniques, strategic roadmapping for AI data bottlenecks, and operational excellence by partnering with various internal teams.
About the role
About the Role
As a Director on the Research team, you will lead a team that focuses on data-centric research that drives the datasets and associated methods that the next generation of models will be trained and evaluated on. From collaborating with researchers at frontier labs to academics at Stanford, Berkeley, UW, you and your team will bridge the gap between cutting edge research and real-world AI development.
Main Responsibilities
- Team Building & Leadership: Recruit for and lead a team of applied researchers, setting the team’s culture and setting a high standard for quality and velocity
- Frontier Data Research: Collaborate with academic and industry-leading AI labs to define the data-centric techniques that will help power the next generation of foundation models.
- Strategic Roadmapping: Anticipate the next bottlenecks in the AI data (e.g., automated RLHF, agentic evaluation, or specialized model alignment) and pivot the team to develop the programmatic solutions that address them
- Operational Excellence: Partner with the Go-to-Market, Operations and Product teams to enhance current state and drive the roadmap for what the company will focus on next
What We’re Looking For
- 8+ years of experience in applied AI, research or machine learning roles, with at least 6+ years of experience managing technical teams
- A player coach who is willing to be hands-on with coding, research, customer-facing engagements
- A proven track record of thriving in fast-paced, ambiguous environments, comfortable managing competing priorities across cross-functional stakeholders in Product, Engineering, and GTM
- Enjoys solving real-world problems in the data space and bridging research and production
- Strong, practical experience working with LLMs, agentic workflow
- Bonus: Experience with data annotation workflows and/or building internal tooling for them