Before you apply
Listed location: United States
Work arrangement: onsite. A remote label does not confirm worldwide eligibility or visa sponsorship.
Read the employer’s description for qualifications, compensation and work eligibility. Confirm the position is still open on the application page.
Job description supplied by Turing; category and skill labels may be inferred. How our listings work · Report a problem
Job 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.
Engineering Manager
Role Overview
We are seeking an Engineering Manager to lead the development of internal tooling and quality-control systems that power AI training workflows. This role is ideal for a leader 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 scalable platforms supporting data creation, annotation, evaluation, review, 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.
Quality and Efficiency:
- Improve dataset quality, task validation, model evaluation, and production efficiency.
- 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.
Architecture and Standards:
- Own architecture, technical delivery, reliability, security, and engineering standards.
- 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.
Leadership and Mentorship:
- Mentor engineers and establish strong design, testing, and release practices.
- Partner with Operations, Product, and AI specialists to identify bottlenecks and deliver pragmatic solutions.
- Lead teams through urgent, high-pressure delivery schedules while maintaining quality and engineering excellence.
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 leading teams 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 challenges of training and evaluating AI systems.
What Success Looks Like
You lead a team that ships high-quality solutions enabling AI training workflows. You can identify technical bottlenecks, design pragmatic solutions, and guide your team to implement them reliably. You're energized by working across the full stack from infrastructure to application code, and you're excited about the technical challenges of building evaluation and quality-control systems for AI at scale while developing strong engineers.
Values
- We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value.
- We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection
- We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.
Advantages of joining Turing
- Work at the frontier of AI, helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks.
- Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS.
- Bring frontier AI innovation to the enterprise, applying lessons learned from leading AI labs to solve real-world business challenges.
- Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies.
- Move at the pace of AI innovation, with the speed, ownership, and impact of a startup.
Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
For applicants from the European Union, please review Turing's GDPR notice here.
Skills mentioned
Categories
Frequently asked questions
Is the Engineering Manager position at Turing remote?
The Engineering Manager role at Turing does not have a confirmed remote arrangement in our data. Check the employer description for its work location.
What type of employment is the Engineering Manager role?
Turing is hiring for a full-time Engineering Manager position.
Which skills are mentioned for the Engineering Manager job at Turing?
Detected skill labels include Python, Kubernetes, Docker, React, Reinforcement Learning, Spark, LangChain, Terraform. Check the employer description to distinguish required skills from preferred experience.
How do I apply for the Engineering Manager position at Turing?
You can apply for the Engineering Manager role directly through Turing's official application link provided on this page.