Requirements

• Proven hands-on experience in building ML systems from end to end, including testing, monitoring, scaling, and measuring the impact; 5+ years in applied data science or ML engineering, ideally in a product setting.
• Strong engineering fundamentals: mastery of Python and SQL/PySpark, clean code practices, and experience with modern ML tooling and cloud infrastructure (AWS, SageMaker, Airflow, Docker, MLflow).
• Production experience with a deep learning framework (PyTorch, TensorFlow or JAX)
• Experience with experimentation design and causal inference, and the judgement to know when a significant result is not yet a final decision.
• Strong product sense and proactive ownership, with the ability to turn ambiguous problems into measurable solutions and drive them from discovery to production impact.
• Adaptable and comfortable wearing several hats in a small team: modelling, pipeline engineering, stakeholder work and mature system maintenance.

What You'll Be Doing

• Take ownership of the ML systems you work on, from notebook prototype to deployed, monitored, retrained service: keep the mature ones healthy and build the new ones.
• Design, train, and deploy models across tabular, image, video and sensor data, choosing the right tool for each.
• Turn modelling output into operational and pricing rules with clear economics, and validate them through experiments and quasi-experimental analysis before they reach the fleet or the customer.
• Collaborate cross-functionally with Software Engineers, Data Scientists, Product Managers, Operations, and the ML Platform team to productionise and monitor ML solutions.
• Write the documentation, runbooks and diagnostics that let others operate and extend your systems.

Perks and Benefits

• Play a direct role in shaping the future of mobility.
• Make an impact on millions of customers and partners across 850+ cities in 50+ countries.
• Work in fast-moving, autonomous teams with talented and supportive colleagues.
• Accelerate your professional growth with unique career opportunities.
• Receive a rewarding salary and stock option package that lets you focus on doing your best work.
• Enjoy the flexibility of hybrid working, with a minimum of (insert X) days in the office each week to foster strong connections and teamwork.
• Take care of your physical and mental health with our wellness perks.