MLE, Data Enrichment

📋 Description

• Work with internal customers to define scene and scenario attributes, dataset requirements and
• Design and refine annotation tasks and labelling instructions, using pilots, annotator agreement
• Curate and deliver ground-truth datasets for other teams to train and evaluate models, addressing
• Build and evaluate computer vision models that draw on Wayve's World Foundation Model to identify
• Use error analysis to identify gaps in data, labels and model performance, and test approaches to

🎯 Requirements

• Practical experience developing and evaluating computer vision models for image or video
• Strong Python programming skills and experience with a modern machine learning framework such as
• Experience curating training and evaluation datasets and assessing annotation quality, with an
• Experience taking machine learning models beyond experimentation into use, with reproducible
• Ability to investigate model failures and determine whether improvements need better data, clearer
• Ability to translate an ambiguous customer request into clear technical deliverables and quality

🎁 Benefits

• Salaries benchmarked against the market annually
• Meaningful equity, sharing in the ownership and long term success of Wayve
• Relocation support and visa sponsorship where applicable
• Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
• Learning and development budgets with support for training, conferences and growth
• Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave