About the position
You will work as part of our Frontier Data team to build data to enhance LLM agent capabilities. The team partners closely with leading-edge research and development efforts from AI labs to scale up human data in new agent environments. Data products we currently support include agents focused on software engineering, computer use, and multiple-faceted tool use. The Agent Data team supports the entire lifecycle of human data input for agents: Initial data architecture, prototyping, and definition; Development of collection tooling, quality control, and management; Operational scaling across thousands of expert human data collectors; Performance evaluation frameworks to prove data efficacy; Testing environments and benchmarking. As Engineering Manager, you will manage the team of engineers and work closely with our customers, internal ML researchers, and operators to define, build, and support these data products.
Responsibilities
- Manage the engineering team and drive technical delivery for Agents Data
- Deliver experiments at a high velocity and level of quality to engage our customers
- Work across the entire product lifecycle from conceptualization through production
- Build features end-to-end: front-end, back-end, system design, debugging and testing
- Influence the culture, values, and processes of a growing engineering team
- Inspire and mentor less experienced engineers
Requirements
- At least 5 years of relevant experience and at least 2 years of experience managing engineers is preferred
- Experience working on Agent-related products or research
- Track record of shipping high-quality products and features at scale
- Desire to work in a very fast-paced environment
- Ability to turn business and product ideas into engineering solutions
- Excellent problem-solving skills, and be able to work independently or as part of a team
- Excited to join a dynamic, hybrid team in either San Francisco or New York City
Benefits
- Comprehensive health, dental and vision coverage
- Retirement benefits
- Learning and development stipend
- Generous PTO
- Commuter stipend
