ML/AI Engineer

Turing

14h

About The Position

Turing is seeking a hands-on ML / AI Engineer to build the tooling, evaluation infrastructure, and quality-control systems that support AI training workflows. The role spans application development, infrastructure, and applied AI. The engineer will join a rapidly growing team working on complex AI systems in a startup-paced environment with high expectations and short timelines. Turing seeks someone who takes ownership, has shipped production systems, and welcomes fast-paced, ambiguous work.

The position involves building tools and platforms for dataset creation, annotation, evaluation, validation, and delivery; developing AI agents, task environments, evaluation pipelines, and automated quality-control systems; and improving the reliability, scalability, and efficiency of AI training and data-production workflows. The engineer will collaborate with research and domain experts, help make technical design and architecture decisions, and investigate production issues through durable fixes.

The role calls for strong software engineering fundamentals, practical judgment balancing speed and quality with scalability and maintainability, and the ability to work independently across infrastructure and application code. Turing describes its values as being client first, working at startup speed, and being AI forward. The company highlights the opportunity to work with frontier AI labs and enterprise clients, contribute to AI research, collaborate with experienced colleagues, and work with startup-level speed, ownership, and impact. Turing is an equal opportunity employer and encourages applicants who are excited about the role even if their experience does not align perfectly with every qualification.

Requirements

• Strong software engineering fundamentals and a proven track record of shipping production systems.
• Experience working independently and effectively in fast-paced, ambiguous environments.
• 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 challenges of training and evaluating AI systems.
• Technical skills listed include web development with Node.js, React, NestJS, Next.js, or Express; Python engineering and data science with FastAPI, NumPy, or Jupyter notebooks; large-scale data generation and data-pipeline orchestration; infrastructure with Kubernetes, Docker, Pulumi, Terraform, or infrastructure-as-code; AI engineering with LangChain, LiteLLM, RL Gyms, LoRA and fine-tuning, AI agents, or Harbor; and dataset validation, evaluation frameworks, automated testing, or QC tooling.

Nice To Haves

• Experience with data-processing frameworks such as Spark, Beam, or Dataflow is preferred.
• Experience with statistical analysis, data visualization, and data manipulation.

Responsibilities

• Build tools and platforms for dataset creation, annotation, evaluation, validation, and delivery.
• Design and implement APIs, internal applications, and developer tooling to enable efficient workflows.
• Develop maintainable, well-tested code that scales with growing demands.
• Develop AI agents, task environments, evaluation pipelines, and automated quality-control systems.
• Build and iterate on evaluation frameworks to ensure the quality and reliability of AI training outputs.
• Collaborate with research and domain experts to translate requirements into practical solutions.
• 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.
• Investigate production issues, identify root causes, and implement durable fixes.
• Work independently to solve complex technical challenges in a fast-paced, ambiguous environment.

Benefits

• Opportunity to work at the frontier of AI with leading AI labs.
• Opportunity to contribute to leading-edge AI research and showcase work at conferences such as ICLR, ICML, and NeurIPS.
• Opportunity to apply AI innovations to real-world enterprise challenges.
• Opportunity to collaborate with and learn from colleagues with AI experience at Google, Meta, Amazon, and other leading technology companies.
• Startup-level speed, ownership, and impact.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed