Senior Technical Program Manager - AI Platform Performance & Reliability at Nuro

<p><strong>Who We Are </strong></p> <p>Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides.<br><br>Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles.<br><br>With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected.<br><br>Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors.</p> <p><strong>About the Role<br></strong></p> <p>We’re looking for a <strong>Technical Program Manager (TPM)</strong> to drive cross-functional alignment and execution for <strong>AI Platform </strong>programs at Nuro. This role sits at the intersection of <strong>Systems Engineering, Platform, Data Science and Autonomy</strong> teams - focused on delivering scalable and reliable verification & validation (V&V) tools that enable systems readiness for <strong>driverless deployment</strong>.</p> <p>You’ll own the end-to-end lifecycle of systems tooling initiatives: defining requirements, managing priorities, coordinating integration with simulation and autonomy stacks, and ensuring test and validation infrastructure meets the evolving needs of driverless programs.</p> <p><strong>About the Work<br></strong></p> <ul> <li>Own the reliability metrics that gate driverless readiness and drive them to target.</li> <li>Serve as the primary interface across AI Platform, Systems, Hardware, and Vehicle Ops, running the operating cadence that keeps reliability work aligned and moving.</li> <li>Build and maintain detailed execution plans; track progress, risks, and metrics using internal tools (e.g., JIRA , Confluence, custom dashboards).</li> <li>Drive issue triage and burndown to resolution, ensuring clear ownership and accountability across teams.</li> <li>Translate field failure patterns into engineering and tooling priorities for the platform.</li> <li>Partner with engineering to focus test and validation capacity on the highest-risk failure modes. Identify testing and validation gaps and improve development workflows.</li> <li>Partner with Ops to improve troubleshooting and intervention workflows, reducing time-to-recovery.</li> <li>Maintain execution plans and provide program updates, decision docs, and risk assessments to leadership.</li> <li>Shorten the loop from field failure to validated fix on the fleet.</li> </ul> <p><strong>About You<br></strong></p> <ul> <li>Bachelor’s degree in <strong>Computer Science, Electrical Engineering, Robotics, or a related field</strong>.</li> <li><strong>5+ years</strong> of experience in <strong>technical program management</strong>, <strong>systems engineering</strong>, or <strong>software development</strong> in robotics, automotive, or related technology domains.</li> <li>Proven experience leading cross-functional programs involving multiple engineering disciplines (software, hardware, autonomy, or systems).</li> <li>Strong understanding of <strong>system verification and validation</strong>, testing frameworks.</li> <li>Demonstrated ability to manage complex dependencies, drive alignment, and communicate effectively across technical and leadership audiences.</li> <li>Proficiency with agile program tools (e.g., Jira) and technical documentation platforms (e.g., Confluence).</li> </ul> <p><strong>Bonus Points </strong></p> <ul> <li>Experience with autonomous systems, vehicle platforms, or robotics simulation environments.</li> <li>Familiarity with data and tooling stacks supporting system V&V (e.g., test harnesses, synthetic data generation, regression testing, scenario replay tools).</li> <li>Technical depth in Python, C++, or data tooling pipelines sufficient to engage engineers on design trade-offs.&l

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