Senior Machine Learning Engineer, Vision Models

Highlights

• Build offline scene-understanding models that measure real-world driving performance.
• Create fleet-scale evidence used in validation pipelines and safety cases.
• Mine rare events and assess driving behaviour across geographies and conditions.

What they offer

• Salaries benchmarked against the market annually
• Meaningful equity
• Relocation support and visa sponsorship where applicable
• Hybrid working with access to vehicle workshops and labs
• Learning and development support
• Comprehensive health, family, retirement and wellbeing benefits

Ideal candidate

Ownership-driven ML engineer energized by ambiguous problems and real-world autonomy. You care about rigorous evidence, fleet-scale impact, and mentoring others while shaping how safe driving is measured.

Requirements

• 4+ years in ML engineering with deep-learning models trained and shipped to production
• Hands-on experience with modern computer vision, transformer, multimodal or VLM architectures
• Experience adapting or fine-tuning large pretrained or foundation models
• Proficient in Python and PyTorch or similar framework with large-scale training
• Ability to take ambiguous modelling problems from scoping to measurable solution