Technical Lead Manager, ML Platform Infrastructure

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 with deep expertise in large-scale infrastructure, workload orchestration, as well as batch and streaming data processing systems to join our ML Infrastructure team. In this role, you will lead the evolution of our core platform, ensuring our researchers and engineers have seamless access to the compute and data resources required to build the future of autonomous driving.

You will drive the strategy for automated resource provisioning, high-performance workload scheduling, and efficient feature management. As a TLM, you will balance technical hands-on leadership with people management, mentoring a high-performing team while partnering closely with ML Research and Autonomy teams to eliminate infrastructure bottlenecks and accelerate the Nuro Driver™ development lifecycle.

About the Work

As the TLM for ML Platform Infrastructure, you will build the foundation that powers Nuro’s model development from experimentation to production. This will include:

• Setting Technical Strategy: Defining the roadmap for a unified ML platform that abstracts complex cloud infrastructure.
• Resource Provisioning & IaC: Scaling our automated infrastructure-as-code (IaC) pipelines to manage thousands of GPU/CPU nodes across diverse environments.
• Intelligent Scheduling: Designing and optimizing workload orchestration to maximize hardware utilization, minimize job wait times, and handle massive-scale distributed training.
• Data Dumping & ETL: Designing robust pipelines for the extraction and transformation of petabyte-scale sensor and telemetry data into ML-ready formats.
• Feature Caching & Feature Stores: Implementing robust feature caching and storage solutions to reduce redundant computations and ensure low-latency access to pre-computed features.
• Team Leadership: Mentoring and growing a team of software and systems engineers, fostering a culture of operational excellence and technical innovation.

About You

• Experience: 6+ years of professional experience in ML Infrastructure, Backend Platform Engineering, or Distributed Systems with 3+ years of people/team management experience.
• Resource Provisioning: Deep familiarity with modern Infrastructure-as-Code and provisioning tools (e.g., Terraform, Pulumi, or Cross