Overview
In this role you lead a small team focused on Robotaxi driving performance, while staying deeply technical. You diagnose high-impact road issues and drive fixes through data and model iteration. You own data recipes, model architecture, and evaluation for the driving model, and collaborate cross-functionally to resolve interface challenges. You will write code, run experiments, and shape priorities as the team scales the Robotaxi program. This is a hands-on leadership position at the heart of Wayve’s autonomous driving mission.
Pay / Benefits
- salary benchmarked against the market
- meaningful equity
- relocation support and visa sponsorship
- hybrid working with in-office and remote days
- learning and development budgets
- comprehensive health benefits and wellbeing programs
Responsibilities
- Lead a team of up to five engineers, balancing people leadership with hands-on technical work
- Diagnose on-road high-impact issues, identify root causes, and implement fixes via data/model iteration
- Own changes to data pipelines, model architecture, evaluation, and release readiness for the driving model
- Collaborate with other teams to resolve cross-functional model-vehicle interface issues
- Act as a key hands-on developer, writing code and running experiments while setting team priorities
- Contribute to end-to-end development of the Robotaxi driving model powering global launches
- Scale driving performance across cities and platforms while meeting KPIs
- Drive data-led iteration using on-road and off-road evaluations to close performance gaps
- Grow and shape a small high-impact team as the Robotaxi program expands
Key requirements
- Managed engineers before and able to lead while remaining technically hands-on
- Strong technical proficiency in Python and model/data iteration
- Experience deploying production ML models and improving live systems
- Focus on production ML over initial research or exploration
- people leadership
- cross-functional collaboration
- strong communication
- Python (hands-on)
- ML productionization
- model iteration and evaluation
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