MLE, Data Enrichment

Highlights

• Build ground-truth datasets describing complex driving scenes across Wayve's corpus.
• Help find rare scenarios and expose gaps to improve safety of AI Driver products.
• Tackle vision problems spanning road geometry, road users and driving behaviour.

What they offer

• Salaries benchmarked against the market annually
• Meaningful equity sharing in long-term success
• Relocation support and visa sponsorship where applicable
• Hybrid working with core hours and hands-on workshop time
• Learning and development budgets for training and conferences
• Comprehensive health, dental, parental leave, pension and wellbeing benefits

Ideal candidate

A pragmatic computer vision engineer who loves turning ambiguous real-world problems into high-quality datasets and models. You take ownership, dig into failures, and care about building safe autonomy at scale.

Requirements

• Practical experience developing and evaluating computer vision models for image or video understanding
• Strong Python skills and experience with modern ML framework such as PyTorch
• Experience curating training and evaluation datasets and assessing annotation quality
• Experience taking ML models into use with reproducible training, evaluation and inference
• Ability to investigate model failures and translate ambiguous requests into technical deliverables