Job description

Who We Are 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. 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. 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. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors About the Role Evaluation Infrastructure plays a critical role at Nuro, directly enabling L4 driverless deployment. The team supports two demanding workloads: day-to-day Autonomy Evaluation that powers rapid software iteration, and large-scale Driverless Safety Validation that produces the rigorous evidence required to deploy autonomy on public roads. The Evaluation Infrastructure team builds the metrics framework, evaluation pipelines, introspection tooling, and analysis products that turn raw on-road and simulation logs into actionable insight. Our metrics stack spans both heuristic and ML-based approaches, covering everything from low-level component accuracy to end-to-end behavior quality. The platform empowers autonomy and Systems & Safety teams to run complex evaluations and validations across a wide range of configurations and scales, producing the high-fidelity metrics that drive both short-term iteration and long-term release confidence — in close partnership with Simulation and the broader AI Platform. As the Technical Lead, you will lead the team with deep technical guidance and rigor, setting the technical bar, shortening the time-to-signal for evaluation and the time-to-confidence for validation, so that both autonomy and Systems & Safety teams can iterate fast while deploying software safely. About the Work Build and own a unified metrics, evaluation, and validation platform — pipelines, introspection tooling, and analysis products that turn on-road and simulation logs into high-fidelity signals for autonomy iteration and driverless safety validation Drive the technical bar for metric quality across both heuristic and ML-based approaches; invest in the scale, reliability, and CI/CD of the evaluation stack to shorten time-to-signal for evaluation and time-to-confidence for validation, and to meet high SLAs for downstream stakeholders Mentor and grow the Evaluation Infrastructure team, and champion AI-native engineering practices that compound team velocity and code quality Partner with Product, Autonomy, Systems & Safety, and Simulation teams to define and execute the vision and strategy for evaluation at Nuro About You You have a degree in B.Sc or M.Sc., plus 4 years of relevant work experience Domain experience: Strong fluency in distributed systems, large-scale data and ML evaluation pipelines, metrics frameworks (heuristic and/or ML-based), and analytics platforms Engineering leadership: Experience setting technical vision, roadmap, and prioritization for a team operating at the intersection of autonomy, safety, and data infrastructure; a clear, concise communicator who partners effectively with PMs, engineers, and cross-functional stakeholders across Autonomy, Systems & Safety, and Simulation Technical excellence: Ability and willingness to deep-dive into implementation; sets the technical bar for metric quality, pipeline rigor, and safety-critical engineering practice across the broader software organization; strong proficiency in Python, C++, or similar languages AI-native mindset: Daily user of modern AI coding assistants and agentic tools (Claude Code, Cursor, and similar), with strong intuition for where they accelerate engineering work and where they don't; eager to apply LLMs and ML systems to evaluation problems, from automated triage and metric generation to natural-language analysis of fleet behavior; raises the team's productivity, code quality, and signal density through thoughtful AI integration Bonus Points Knowledge of data engineering, and its tooling and best practices Knowledge of batch and streaming data processing, warehousing, and analytics solutions Experience with data workflow orchestration platforms Prior experience building evaluation, validation, or analytics platforms, ideally in autonomy, robotics, or safety-critical systems At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $193,930,200 and $291,150/year 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.

Requirements

Must-haves

You have a degree in B.Sc or M.Sc., plus 4 years of relevant work experience
Domain experience: Strong fluency in distributed systems, large-scale data and ML evaluation pipelines, metrics frameworks (heuristic and/or ML-based), and analytics platforms

Nice-to-haves

Knowledge of data engineering, and its tooling and best practices
Knowledge of batch and streaming data processing, warehousing, and analytics solutions
Experience with data workflow orchestration platforms
Prior experience building evaluation, validation, or analytics platforms, ideally in autonomy, robotics, or safety-critical systems

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