Senior Machine Learning Engineer, Data Enrichment (Autonomous Driving)

robotics jobs uk • United Kingdom

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AI Summary

Develop ground-truth datasets and classifiers for Wayve’s AI-driven autonomous driving systems, focusing on computer vision, spatial relationships, and driving behavior. Collaborate with cross-functional teams to refine annotation tasks, evaluate model performance, and improve perception and driving models for safety and reliability. Bridge technical and business needs by translating ambiguous requirements into measurable deliverables and quality criteria.

Key Highlights

Build and refine ground-truth datasets and classifiers for complex driving scenes using Wayve’s World Foundation Model

Design annotation tasks, labeling instructions, and quality control workflows to ensure data accuracy and coverage

Develop and deploy computer vision models for scene attribute identification, spatial relationships, and driving behavior analysis

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Key Responsibilities

Define scene and scenario attributes, dataset requirements, and measurable acceptance criteria for annotations and classifiers in collaboration with internal customers

Design and refine annotation tasks, labeling instructions, and quality control processes using pilots, annotator agreement, and expert review

Curate and deliver ground-truth datasets for model training and evaluation, addressing rare scenarios, class imbalance, and global coverage

Build and evaluate computer vision models to identify scene attributes and driving behaviors, leveraging Wayve’s World Foundation Model

Conduct error analysis to identify gaps in data, labels, and model performance, proposing improvements for data, labels, or modeling approaches

Integrate classifiers with enrichment infrastructure to run inference across driving data for corpus analysis and scenario mining

Improve reusable tools for annotation, training, evaluation, and inference, and document dataset/classifier quality and limitations

Technical Skills Required

Python Computer Vision Machine Learning Frameworks (PyTorch)

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Benefits & Perks

Market-benchmarked salaries

Meaningful equity

Relocation support and visa sponsorship where applicable

Hybrid working with core hours

Comprehensive benefits including health insurance, dental, and retirement plans

Learning and development budgets

Access to vehicle workshops and labs

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Nice to Have

Experience with 3D geometry, multi-camera systems, or temporal scene understanding

Background in autonomous driving, ADAS, or robotics

Adapting pretrained/foundation or vision-language models

Human annotation workflows, active learning, or model-assisted labeling

SQL, distributed data processing, and batch inference

Job Description

Before the detail, here's the challenge you'd help us solve.We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.Here’s what this particular role covers.

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