Field Engineer, AI Labs
$175k - $232k • Remote • New York, New York, United States; San Francisco, California, United States; Seattle, Washington, United States
Posted 8h ago
Job Location
New York, New York, United States; San Francisco, California, United States; Seattle, Washington, United States
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Engineer
About the job
Turing builds the training and evaluation data that powers the world's leading frontier AI labs. As these labs push the boundaries of AI, they rely on us to assess their newest models against benchmark datasets, identify failure points, and determine what data will improve their capabilities. As a Field Engineer, AI Labs, you will be the technical representative of Turing to these frontier research teams, operating at the intersection of client-facing solutions engineering and hands-on AI evaluation. You will connect new model endpoints, execute comprehensive evaluations across Turing's datasets, synthesize performance metrics into actionable insights, and present these findings directly to client researchers and technical leaders. This is a high-velocity, high-agency role for a technically adept individual who excels at customer interaction, running benchmarks against model APIs, and ensuring precise data delivery.
Responsibilities
- Connect frontier model APIs and inference endpoints to evaluation harnesses.
- Execute large-scale benchmark runs across proprietary Turing datasets.
- Analyze evaluation results to identify failure cases and capability gaps.
- Serve as the technical counterpart to sales leads in client discussions.
- Translate complex evaluation metrics into client-facing reports and presentations.
- Answer technical questionnaires and RFIs from lab researchers.
- Surface client feedback and benchmark requirements to internal R&D teams.
- Query, manipulate, and manage data pipelines within Turing's internal data infrastructure.
- Curate custom data subsets based on specific criteria.
- Audit data provenance and maintain dataset specifications.
- Own last-mile data delivery, schema alignment, and packaging to meet client specifications.
- Verify data deliverables adhere to rigorous validation standards.
Requirements
- 1 to 5 years of professional experience in data science, AI/ML engineering, solutions engineering, or data analytics with a transition into generative AI.
- Strong Python proficiency, including working with REST/gRPC model APIs, inference endpoints (OpenAI, Anthropic, Bedrock, vLLM), pandas, and SQL.
- Practical experience with model evaluation, benchmark design, or LLM-as-a-judge pipelines.
- High agency and a startup mindset, with experience owning projects end-to-end and delivering under tight deadlines.
- Exceptional written and verbal communication skills.