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.
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.
- 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.
- 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 Required
- Strong software engineering fundamentals with a proven track record of shipping production systems.
- Experience leading teams effectively in fast-paced, ambiguous environments.
- Ability to balance speed, quality, scalability, and maintainability in technical decisions.
- Strong debugging and problem-solving skills.
- Strong communication skills with cross-functional teams.
- Interest in the evolving challenges of training and evaluating AI systems.
- Proficiency in large-scale data generation and data pipeline orchestration.
- Experience with Spark, Beam, or Dataflow.
- Experience with statistical analysis, data visualization, and data manipulation.
- Experience with Node.js, React, NestJS, Next.js, or Express.
- Experience with Python, FastAPI, NumPy, or Jupyter notebooks.
- Experience with Kubernetes, Docker, Pulumi, Terraform, or infrastructure as code.
- Experience with LangChain, LiteLLM, RL Gyms, LoRA, fine-tuning, AI agents, or Harbor.
- Experience with dataset validation, evaluation frameworks, automated testing, and quality-control tooling.
Turing Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Turing and has not been reviewed or approved by Turing.
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Fair & Transparent Compensation — Feedback suggests USD-denominated pay and access to higher-paying clients can outpace local benchmarks for many non‑U.S. developers. Payout timing and processing are described as predictable once engagements begin, which supports confidence in earnings.
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Wellbeing & Lifestyle Benefits — Feedback suggests remote‑first work with flexible hours is a consistent positive that enhances day‑to‑day balance. The ability to work from anywhere and maintain autonomy is frequently highlighted as part of the overall rewards experience.
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Healthcare Strength — Feedback suggests some U.S. corporate roles include comprehensive health benefits, with individual accounts referencing employer‑covered medical insurance. These signals indicate stronger healthcare support for certain employee populations.
Turing Insights
What We Do
We now live in a remote-first world and every company is in a race to find the best remote engineers. There are so many amazing engineers all over the world. Turing’s mission is to help unleash the world’s untapped human potential. More than 300 companies, including those backed by Google Ventures, Bloomberg, Andreessen, Founders Fund, and Kleiner are already using Turing to spin up their engineering dream teams. Turing’s hiring platform combines the planetary reach and AI to deliver your ideal engineers in order to help you spin up your engineering dream team. Our deep matching intelligence finds the best Turing developers across 100+ skills like React, Node, Python, Golang, Angular, Swift, Java, and many more. As part of our rigorous vetting process, we also review software engineers’ technical abilities, English skills, and remote working capabilities. Turing ensures time zone overlap, transparency, and reliable communication in order to make remote development easy for you after the match. The Turing team has deep expertise in AI and building engineering dream teams in the U.S. at top companies. Turing company is backed by well-known investors like Facebook’s initial CTO (Adam D’Angelo), executives from Google, Facebook, Amazon, Twitter, Founders Fund (investors in Facebook, Tesla, Asana, etc). Turing.com is led by serial A.I. entrepreneurs Jonathan Siddharth and Vijay Krishnan, their last A.I. firm leveraged remote talent and had a successful acquisition.
