The Role
You will be responsible for developing cutting-edge human-in-the-loop systems that move beyond labeling to guiding experts on complex, multi-step tasks. From rapidly prototyping and testing methods with 1000s of users to innovating core data-centric methods, you will have the opportunity to lead how data that powers the next generation of frontier models is created and curated.
What You'll Do
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
The Research-to-Product Bridge: Act as the primary link between Research, Product, and Engineering. You will oversee the development of experimental POCs to improve workflow efficiencies and ensure these innovations are successfully hardened and integrated into the platform
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 Operations team to validate research-driven workflows in real-world production environments, ensuring they scale across diverse and complex domain-specific tasks
What We're Looking For
5+ years of experience in applied AI, research or machine learning roles, with at least 4+ 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
Location: Bay Area (Hybrid or In-Office)
Reports to: Head of Research (Co-founder)