Field Engineer, AI Labs
- Salary
- ₹22–38 LPA
- Location
- San Francisco, US
- Experience
- Intermediate
About the company & role
About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . About the role Turing builds the training and evaluation data powering the world’s leading frontier AI labs. As these labs push the frontier, they bring us their newest models and ask the critical question: how does our model perform against your benchmark datasets, where does it fail, and what data will make it climb the hill? As a Field Engineer, AI Labs , you are the technical face of Turing to frontier research teams. You sit at the exact intersection of client-facing solutions engineering and hands-on AI evaluation. When a frontier lab provides a new model endpoint, you wire it up, run comprehensive evals across Turing’s datasets, synthesize raw performance metrics into actionable intelligence, and present those findings directly to client researchers and technical leaders. This is not a pure research engineering seat and not a traditional forward-deployed IT role. It is a high-velocity, high-agency solutions engineering role for a technically fluent, dependable builder who thrives on talking to customers, running benchmarks across model APIs, and packagi