# ML/AI Engineer at Turing

Turing is hiring an ML/AI Engineer. Level rates it Builds AI ●●●●; you can [apply on Turing](https://jobsbylevel.com/go/b06b5042-2763-4bed-9a43-66e381e52720?utm_medium=ai-agent).

AI Level 4, AI centrality 91 out of 100. United States.

## Details

- Company: [Turing](https://jobsbylevel.com/companies/turing)
- AI level: AI Level 4 (score 91 out of 100)
- Location: United States
- Posted: November 10, 2026
- Apply: https://jobsbylevel.com/go/b06b5042-2763-4bed-9a43-66e381e52720?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=ml-ai-engineer-at-turing-3acc9b

## Prepare for this job

The job page lists 5 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/ml-ai-engineer-at-turing-3acc9b

## Description

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 . Machine Learning Engineer Role Overview We are seeking a hands-on ML / AI Engineer to build the tooling, evaluation infrastructure, and quality-control systems that power AI training workflows. This role is ideal for an engineer who enjoys working across application development, infrastructure, and applied AI. You will be part of a rapidly growing team solving complex problems in AI systems, working in a startup-paced environment with high expectations and short timelines. The ideal candidate is someone who takes ownership beyond what their role technically requires, has a track record of shipping production systems, and is excited by the intensity of a fast-paced, ambiguous environment rather than looking for stable, predictable work. Key Responsibilities Tooling and Platform Development: Build tools and platforms for dataset creation, annotation, evaluation, validation, and delivery. Design and implement APIs, internal applications, and developer tooling that enable efficient workflows. Develop maintainable, well-tested code that scales with growing demands. AI Systems and Evaluation: Develop AI agents, task environments, evaluation pipelines, and automated quality-control systems. Build and iterate on evaluation frameworks that ensure quality and reliability of AI training outputs. Collaborate with research and domain experts to translate requirements into practical solutions. Infrastructure and Scalability: Improve the reliability, scalability, and efficiency of AI training and data production workflows. Design and implement data pipelines for dataset creation, annotation, and delivery at scale. Contribute to technical design and architecture decisions that balance speed, quality, and maintainability. Production Support and Problem Solving: Investigate production issues, identify root causes, and implement durable fixes. Write maintainable, well-tested code with a pragmatic approach to quality and scalability. Work independently in a fast-paced, ambiguous environment to solve complex technical challenges. Technical Skills Web Development - Node.js, React, NestJS, Next.js, Express Python Engineering and Data Science - FastAPI, NumPy, Jupyter notebooks. Proficiency in large-scale data generation and data pipeline orchestration. Frameworks like Spark, Beam, or Dataflow preferred. Statistical analysis, data visualization, and data manipulation. Infrastructure - Kubernetes, Docker, Pulumi, Terraform, infrastructure-as-code AI Engineering - LangChain, LiteLLM, RL Gyms, LoRA and fine-tuning, AI agents, and Harbor Quality Systems - Dataset validation, evaluation frameworks, automated testing, and QC tooling Qualifications Strong software engineering fundamentals with a proven track record of shipping production systems. Experience working independently and effectively in fast-paced, ambiguous environments. Demonstrated ability to balance speed, quality, scalability, and maintainability in technical decisions. Strong debugging, problem-solving, and communication skills with cross-functional teams. Interest in the evolving

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Source: https://jobsbylevel.com/jobs/ml-ai-engineer-at-turing-3acc9b

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Level. https://jobsbylevel.com/jobs/ml-ai-engineer-at-turing-3acc9b.

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