Tech Lead, Autonomy Performance - Robotaxi

Wayve Wayve · Robotics · London, United Kingdom · Vehicle SW Engineering

Tech Lead for Autonomy Performance in a Robotaxi program, focusing on defining and owning the performance measurement framework, issue detection, prioritization, and driving improvements across ML models and robot software. This role involves cross-functional leadership and hands-on debugging in Python/C++/SQL to ensure the product meets release readiness and maintains performance over time.

What you'd actually do

  1. Own and evolve the autonomy performance measurement framework for Robotaxi (driving + pick-up / drop-off), including the metrics, dashboards, and narrative used by leadership to make ship/no-ship decisions
  2. Build and run the end-to-end performance improvement loop: detect issues, triage and prioritise, drive root-cause investigations, and ensure fixes land across model, robot software, backend, and evaluation tooling
  3. Lead cross-functional execution across AV core, evaluation/validation, robotics, robot software, triage/systems, and SRE—often without direct reporting authority—aligning roadmaps to performance outcomes
  4. Define and enforce performance release gates and regression detection for production deployments; own readiness calls, post-release monitoring, and follow-through on incidents/regressions
  5. Be hands-on in the data and code when needed (Python/C++/SQL) to accelerate debugging, validate hypotheses, and unblock delivery

Skills

Required

  • Demonstrated cross-functional engineering leadership
  • Strong product and customer orientation
  • Strong autonomy/robotics performance debugging experience
  • Strong technical foundations in learned systems / ML-driven robotics
  • Production fluency in Python, C++ and SQL

Nice to have

  • Experience owning or co-owning releases to a fleet of robots/vehicles in production
  • Familiarity with modern data/observability stacks used in autonomy programs
  • Track record of building scalable triage systems and performance programs

What the JD emphasized

  • own the autonomy performance bar
  • performance release gates
  • regression detection
  • production deployments
  • real-world issues
  • time-series / real-time signals
  • safety- or mission-critical environments

Other signals

  • owns autonomy performance measurement framework
  • build and run end-to-end performance improvement loop
  • define and enforce performance release gates
  • hands-on in data and code