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Technical Lead Manager, ML Training Infrastructure

Work from home Full-time role Hiring

Who We Are Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale—empowering a safer, richer, and more connected future.

About the Role

Nuro is seeking an experienced Technical Lead Manager to own the vision for our ML Training stack. You will lead a team of 6+ engineers to optimize distributed training, job scheduling, model component libraries, and improve upon our performance analysis tools. In this role you will enable models to train faster and more efficiently – accelerating our self-driving roadmap of commercial and personal mobility. About the Work As TLM for Nuro's ML Training Infrastructure, you will define and execute the ML Framework roadmap, and drive initiatives in distributed training and efficiency optimizations to scale deep learning models. This will include:

  • Define and drive the ML framework roadmap, setting technical direction for the Training Infrastructure team.
  • Build and maintain a scalable, distributed training platform with an emphasis on efficiency, determinism, and reproducibility for large-scale training jobs.
  • Detect, diagnose, and resolve performance bottlenecks across training workflows, including input data pipelines and distributed training loops.
  • Optimize scheduling, training performance, resource utilization, and ensure consistent, reproducible model training outcomes.
  • Mentor and grow a high-performing team, fostering technical excellence and collaboration.
  • Drive improvements in software quality that measurably raise reliability, efficiency, reproducibility, and determinism.

About You

  • 6+ years of professional or research experience in ML infrastructure, distributed training, or ML systems engineering.
  • Experience driving complex technical initiatives with stakeholder engagement.
  • Proven experience leading and growing engineering teams, with a track record of mentoring and inspiring technical talent.
  • Expertise in PyTorch; familiarity with TensorFlow, and experience optimizing training performance (e.g., host offloading, quantization, reduced-precision training).
  • Strong collaboration and communication skills, with a passion for exploring and promoting new approaches and technology.

Bonus Points

  • Hands-on experience with CUDA, Triton, XLA, TPUs.
  • Familiarity with ML compilers, ONNX, and intermediate representations.
  • Experience with containerization (Docker), orchestration (Kubernetes), and ML pipeline tools (Airflow).
  • Practical experience with JAX.

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $222,775 and $333,925 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics. #LI-DNP Apply tot his job Apply To this Job

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