# MLE, Data Enrichment

**Company**: Wayve
**Location**: London
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Automotive

**Apply**: https://jobs.ashbyhq.com/wayve/dbbb7014-e5c0-487f-80bf-ce9d0e9f7566?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_da3d2178-a45

## Description

We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future.

As a Machine Learning Engineer, Data Enrichment, you will tackle computer vision problems spanning road geometry, spatial relationships, road users and driving behaviour.

Your day-to-day:

- Work with internal customers to define scene and scenario attributes, dataset requirements and measurable acceptance criteria for annotations and classifiers

- Design and refine annotation tasks and labelling instructions, using pilots, annotator agreement and expert review to resolve ambiguity and measure quality

- Curate and deliver ground-truth datasets for other teams to train and evaluate models, addressing rare scenarios, class imbalance and coverage across countries and vehicle platforms

- Build and evaluate computer vision models that draw on Wayve's World Foundation Model to identify scene attributes and driving behaviours

- Use error analysis to identify gaps in data, labels and model performance, and test approaches to improve them

What you'll be working on:

- Ground-truth datasets and classifiers that describe road geometry, spatial relationships, road users and driving behaviour

- Integrating classifiers with enrichment infrastructure to run inference across existing and newly collected driving data, making predictions available for corpus analysis and scenario mining

- Improving reusable tools for annotation, training, evaluation and inference

- Documenting dataset and classifier quality, and communicating limitations to colleagues across disciplines

You should apply if:

- You have practical experience developing and evaluating computer vision models for image or video understanding, including interpreting spatial relationships in visual data

- You have strong Python programming skills and experience with a modern machine learning framework such as PyTorch

- You have experience curating training and evaluation datasets and assessing annotation quality, with an understanding of class imbalance, data leakage and representative evaluation

- You have taken machine learning models beyond experimentation into use, with reproducible training, evaluation and inference

- You can investigate model failures and determine whether improvements need better data, clearer labels or changes to the modelling approach

- You can translate an ambiguous customer request into clear technical deliverables and quality criteria, and communicate performance and limitations to colleagues from different disciplines

## Skills

### Required
- Python
- PyTorch
- computer vision
- machine learning

### Nice to have
- 3D geometry
- multi-camera systems
- temporal scene understanding
- autonomous driving
- ADAS
- robotics
- SQL
- distributed data processing
- batch inference

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Source: [Apply at jobs.ashbyhq.com](https://jobs.ashbyhq.com/wayve/dbbb7014-e5c0-487f-80bf-ce9d0e9f7566?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)