MLE, Data Enrichment

Wayve; London (KY); Hybrid; USD 94,000 - 161,000; Full time

Benefits offered by this job

Health insurance

Relocation support

Hybrid work model

Pension plan

Job summary

Wayve is seeking a Machine Learning Engineer, Data Enrichment to advance computer vision models and curate ground-truth datasets across diverse driving scenarios. You will work with internal customers to define dataset requirements and acceptance criteria for annotations and classifiers, ensuring data quality and coverage across platforms and countries.

The role emphasizes building models with Wayve's World Foundation Model, analyzing errors, and translating ambiguous requests into concrete

Qualifications

• Experience developing and evaluating computer vision models for image/video understanding.
• Ability to interpret spatial relationships in visual data.
• Translating customer requests into concrete technical deliverables.

Responsibilities

• Define scene attributes, dataset requirements and acceptance criteria for annotations and classifiers.
• Design and refine annotation tasks and labeling instructions with pilots and expert review.
• Curate and deliver ground-truth datasets across countries and platforms.
• Build and evaluate CV models using Wayve's World Foundation Model to identify scene attributes and behaviours.
• Conduct error analysis to improve data, labels and model performance.

Skills

Python

PyTorch

Computer Vision

Data annotation quality

Model evaluation

Tools

PyTorch

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.

About our Data Enrichment Teams

Our Data Enrichment team builds the ground-truth datasets and classifiers that describe complex driving scenes across Wayve's data corpus. Drawing on Wayve's World Foundation Model, we help teams find rare scenarios, expose performance gaps and develop better perception and driving models, supporting the safety and reliability of Wayve's ADAS and AI Driver products. 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

Desirable: experience with 3D geometry, multi-camera systems or temporal scene understanding; autonomous driving, ADAS or robotics; adapting pretrained, foundation or vision-language models; human annotation workflows, active learning or model-assisted labelling; SQL, distributed data processing and batch inference

Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement.

More about Wayve:

Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines.

Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility.

How we work - Locations & Flexible Working:

Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives.

The Interview Process:

Our process is clear and respectful of your time:

• Initial call / recruiter screen (30 mins)
• Competency Interviews (Programming in Python and MLE domain interview)
• Deep-dive technical interviews (systems design and hiring manager interview)
• Final interview: mission & values alignment.

We’ll always explain the format and work around your availability.

What’s in it for you (Location dependant):

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, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more

A quick, honest note before you apply.

Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one.

If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

For more information visit Careers at Wayve. To learn more about what drives us, visit Values at Wayve DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.