Senior Machine Learning Engineer, Vision Models

Wayve • Sunnyvale, CA

4d • $311,850 - $389,400 • Hybrid

About The Position

Wayve is building the embodied intelligence that moves real vehicles safely and the ecosystem a billion machines will run on in the future. The Measurement team within AI Evaluation builds and qualifies the offline scene-understanding models Wayve uses to measure driving performance after on-road runs and in simulation. Offline modelling provides greater compute, larger models, and access to past and future temporal context, creating unique opportunities to build credible evidence at fleet scale.

Requirements

• 4+ years in ML engineering and have trained and shipped deep-learning models in production.
• Hands-on experience with modern computer-vision, transformer, multimodal, or VLM architectures.
• Adapted or fine-tuned large pretrained or foundation models and understand data, loss, and representation trade-offs.
• Proficient in Python and PyTorch or a similar framework and comfortable with large-scale training.
• Can take ambiguous modelling problems from scoping to a working, measurable solution.

Nice To Haves

• Experience in 3D scene understanding, offline modelling, auto-labelling, temporal or world models, autonomous vehicles, robotics, or distributed training is valuable.

Responsibilities

• Build, train, and fine-tune scene-understanding models for offline measurement.
• Adapt on-vehicle architectures and Wayve foundation models for offline use.
• Improve accuracy and generalisation across vehicle platforms, geographies, and driving conditions.
• Benchmark your models, diagnose failure modes, and use error analysis to guide iteration.
• Define quality bars and statistically credible evidence for validation pipelines and safety cases.
• Collaborate with on-vehicle modelling, evaluation, data curation, and simulation teams.
• Mentor others and contribute to strong machine-learning and engineering practices.

Benefits

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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed