Tech Lead, Autonomy Performance – Robotaxi

Overview

In this high-impact, hands-on Tech Lead role, you’ll steer the autonomy performance bar for Wayve’s Robotaxi program. You’ll translate real-world driving signals into trusted metrics, prioritised issues, and cross-team execution that improves production performance. You’ll shape end-to-end performance for a learned driving system, influencing multiple teams and roadmaps. You’ll work closely with data, robotics, and software teams to ensure safe, scalable deployments while guiding a growing team as the program scales.

Pay / Benefits

• hybrid working policy
• office in London
• inclusive interview experience
• opportunity to scale a program
• hands-on leadership growth
• impactful, mission-driven work

Responsibilities

• Own and evolve the autonomy performance measurement framework for Robotaxi (driving + pick-up / drop-off), including metrics and dashboards used for ship/no-ship decisions
• Build and run end-to-end performance improvement loop: detect issues, triage, root-cause investigate, and ensure fixes land across model, robot software, backend, and evaluation tooling
• Lead cross-functional execution across AV core, evaluation/validation, robotics, robot software, triage/systems, and SRE—often without direct reporting authority
• Define and enforce performance release gates and regression detection for production deployments; own readiness calls, post-release monitoring, and incident follow-up
• Be hands-on in data and code (Python/C++/SQL) to accelerate debugging and validate improvements

Key requirements

• Demonstrated cross-functional engineering leadership across multiple teams to achieve production outcomes
• Strong product and customer orientation aligning metrics to rider experience and launch readiness
• Strong autonomy/robotics performance debugging with real-world issues and time-series signals
• Strong technical foundations in learned systems / ML-driven robotics and data-driven autonomy stacks
• Production fluency in Python, C++ and SQL, with hands-on coding in analytics pipelines

• cross-functional collaboration
• customer orientation
• problem-solving under uncertainty
• learned systems / ML-driven robotics
• Python
• C++

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