Technical Lead (Evaluation Infrastructure)

Join Nuro as a Technical Lead for the Evaluation Infrastructure team, which plays a crucial role in enabling L4 driverless deployment. You will lead the team in building a unified metrics, evaluation, and validation platform, driving technical excellence, mentoring team members, and partnering with cross-functional teams to define and execute the vision for evaluation at Nuro.

• Lead the Evaluation Infrastructure team in building and owning a unified metrics, evaluation, and validation platform.
• Drive the technical bar for metric quality across both heuristic and ML-based approaches, investing in the scale, reliability, and CI/CD of the evaluation stack.
• Mentor and grow the Evaluation Infrastructure team, championing AI-native engineering practices that compound team velocity and code quality.
• 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
• 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
• 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
• 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