Key Notes
Robotaxi launch readiness is measured through a performance framework covering driving, pick-up and drop-off behaviour, release gates and regression detection. The hands-on technical lead needs cross-functional engineering leadership, autonomy or robotics debugging, learned-systems expertise and production Python, C++ and SQL. The London role is full time and hybrid, initially operating as an individual contributor with an expected path to lead a small team.
What You'll Work On
- Own Robotaxi performance metrics, dashboards and leadership narratives used for ship-or-no-ship decisions across driving, pick-up and drop-off.
- Run the performance-improvement loop from issue detection and prioritisation through root-cause investigation and verified fixes across the autonomy stack.
- Align AV core, validation, robotics, robot software, systems and SRE roadmaps around measurable production performance outcomes.
- Define release gates, regression detection, readiness calls and post-release monitoring, using Python, C++ and SQL for hands-on diagnosis.
Why This Role Matters
- Robotaxi public-deployment decisions rely on performance metrics and regression gates that show whether driving and pick-up/drop-off behaviour are ready for release and remain consistent afterwards.
- Robotaxi driving and pick-up/drop-off problems are investigated across model, robot software, backend and evaluation tooling, so fixes address the source of observed performance failures.
What They Are Looking For
- Experience: Cross-functional engineering leadership delivering complex production outcomes without direct line authority is required.
- Experience: Hands-on autonomy or robotics performance debugging using real-world issues and time-series or real-time signals is required.
- Technical: Learned-systems and ML-driven robotics knowledge covering model behaviour, failure modes and measurement pitfalls is required.
- Technical: Production fluency in Python, C++ and SQL for code and analytics-pipeline diagnosis is required.
- Stakeholder: Product and customer judgement connecting technical metrics to rider experience, operations and launch readiness is required.
- Preferred: Fleet-release ownership, autonomy observability stacks or scalable performance-programme experience is desirable.