Opportunity at
TuringField Engineer, AI Labs
Turing operates as a data provider focused on accelerating superintelligence by supplying high-quality datasets, reinforcement learning environments, and research benchmarks to frontier artificial intelligence laboratories and…
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About This Role
Turing operates as a data provider focused on accelerating superintelligence by supplying high-quality datasets, reinforcement learning environments, and research benchmarks to frontier artificial intelligence laboratories and Fortune 500 enterprises. The company bridges frontier research and enterprise deployment, helping organizations build and deploy agentic AI systems. As a Field Engineer, AI Labs, the selected professional serves as the technical representative to frontier research teams. This position sits at the intersection of…
Job Description
Turing operates as a data provider focused on accelerating superintelligence by supplying high-quality datasets, reinforcement learning environments, and research benchmarks to frontier artificial intelligence laboratories and Fortune 500 enterprises. The company bridges frontier research and enterprise deployment, helping organizations build and deploy agentic AI systems.
As a Field Engineer, AI Labs, the selected professional serves as the technical representative to frontier research teams. This position sits at the intersection of client-facing solutions engineering and hands-on artificial intelligence evaluation. Responsibilities include connecting model endpoints to evaluation harnesses, executing benchmark runs across proprietary datasets, synthesizing performance metrics, and presenting findings directly to client researchers and technical leaders. This high-velocity role suits a technically proficient, dependable builder who enjoys customer interactions, benchmarking model APIs, and packaging data deliveries with precision.
The role operates out of New York on a full-time schedule, with base compensation ranging from USD 175,000 to 232,000 annually. In addition to base pay, this position includes eligibility for equity, performance incentives, and comprehensive company benefits. Candidates will collaborate with research scientists and technical executives at prominent AI organizations, directly influencing how next-generation model capabilities are evaluated and improved.
Responsibilities
- Connect frontier model APIs and inference endpoints into evaluation harnesses.
- Execute large-scale benchmark runs across proprietary datasets including reasoning, coding, multimodal, and agentic environments.
- Analyze evaluation results to isolate failure cases, detect behavioral drift, and identify data distributions needed for capability gaps.
- Serve as the technical counterpart to sales leads on calls with frontier AI labs and enterprise teams.
- Translate complex evaluation metrics into reports, client presentations, and technical collateral.
- Answer technical questionnaires and RFIs from lab researchers regarding data design and task curation.
- Surface lab feedback and benchmark requirements back to internal research and development teams.
- Navigate internal data infrastructure to query, manipulate, and move data pipelines.
- Slice and curate custom data subsets based on specific difficulty thresholds and benchmark rubrics.
- Audit data provenance and maintain up-to-date specifications across public catalogs and internal inventories.
- Own last-mile delivery, schema alignment, and packaging to ensure deliverables match technical specifications.
Requirements
- One to five years of professional experience in data science, artificial intelligence and machine learning engineering, solutions engineering, or data analytics with a demonstrated transition into generative AI.
- Strong hands-on Python proficiency utilizing REST and gRPC model APIs, inference endpoints, pandas, and SQL.
- Practical experience with model evaluation, benchmark design, or LLM-as-a-judge pipelines.
- Demonstrated high agency, startup mindset, and experience owning projects end-to-end under tight deadlines.
- Exceptional written and verbal communication skills with the ability to present technical metrics to research scientists.
- Comfort working with command-line tools, internal tooling, and data manipulation workflows.
Qualifications
- Prior experience at an early-stage artificial intelligence startup or high-growth technology company.
- Hands-on experience with evaluation harnesses and agent benchmarks such as Harbor, Terminal-Bench, SWE-bench, or Inspect.
- Experience with fine-tuning models like LoRA or QLoRA, working with open-weights models, or conducting multimodal evaluations.
- Familiarity with data quality control, task verification, or synthetic data generation pipelines.
Core Skills
Benefits
- Annual base salary range of USD 175,000 to 232,000
- Equity eligibility
- Performance incentives
- Comprehensive company benefits
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the location and work model for this role?
The position is based in New York. The posting does not specify any remote, hybrid, or on-site office requirements for this specific location beyond stating the city.
What is the salary range for the Field Engineer position?
The annual base salary ranges from USD 175,000 to 232,000, and the role is also eligible for equity, performance incentives, and comprehensive company benefits.
What type of employment is this?
This is a full-time standard employee position.
What key technical skills are required?
Candidates must have 1 to 5 years of relevant experience, strong hands-on Python proficiency with REST and gRPC model APIs, experience with model evaluation or benchmark design, and strong communication skills.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.