Machine Learning Engineer, Application Software

Highlights

• Advance end-to-end driving models from assisted to autonomous driving.
• Build ML-driven personalised, comfortable and collaborative driving behaviours.
• Create evaluation frameworks for open-loop and closed-loop driving quality.

What they offer

• Salaries benchmarked against the market annually
• Meaningful equity
• Relocation support and visa sponsorship where applicable
• Hybrid working with core hours
• Learning and development budgets with support for training and conferences
• Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement/pension and wellbeing support

Ideal candidate

Seasoned ML engineer passionate about autonomy who thrives with real ownership in ambiguous environments and cares about shipping safe, human-centered driving intelligence.

Requirements

• Extensive, proven track record of shipping deep learning systems to production
• Deep expertise in deep learning, particularly sequential models, control, planning or perception
• Proficient in Python, experienced with C++ or CUDA, and confident with ML frameworks, especially PyTorch
• Strong foundation in software engineering practices and building reliable, maintainable ML systems
• Experience with real-time systems or robotics, ideally simulation-in-the-loop or vehicle-in-the-loop
• Ability to lead technical initiatives across teams, build alignment and mentor engineers