Staff Machine Learning Engineer - Ops

Wayve; Greater London; Hybrid; GBP 75,000 - 110,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Wayve is seeking a Model Integration and Release Engineer to own the ML release lifecycle from development to production. You will shape release processes, review model changes, and ensure quality gates align with safety and performance standards.

You'll collaborate across ML, AI Platform, evaluation, and CI/CD to deliver reliable model updates at scale in our hybrid London-centred setup.

Qualifications

• Significant software integration and release experience with branching strategies and quality gates.
• Experience reviewing model/code changes to ensure alignment with intent and safety.
• Familiarity with ML tooling and deployment workflows (PyTorch, registries, quantisation).

Responsibilities

• Define and evolve release processes, including cadence and configuration management.
• Review model/architecture/code changes against intended outcomes and metrics.
• Assess evaluation results and ensure releases meet quality and safety standards.
• Identify bottlenecks and drive cross-team improvements to releases.

Skills

CI/CD

GitHub Actions

Release management

Model deployment

Education

Bachelor's degree in CS or related field

Tools

PyTorch

TensorRT

Model registries

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 Model Integration and Release Team

Our Model Integration and Release team owns the engineering release process for Wayve's driving models. When research and engineering teams develop new architectures, features, or data changes, we validate that they meet our quality, safety, and performance standards before they reach customers. The team works across ML engineering, AI Platform, evaluation, and CI/CD to protect the model baseline while continually improving how reliably and efficiently we deliver models.

Your day-to-day

• Define and evolve Wayve's model development and release processes, including branching strategies, release cadence, configuration management, and quality gates.
• Review proposed model, architecture, code, and metric changes to ensure the implementation matches its intended outcome.
• Assess evaluation results and determine whether releases meet Wayve's quality and safety standards.
• Identify delivery bottlenecks and work across teams to address their root causes.
• Balance speed and rigour, making informed decisions about when to accelerate delivery and when a release needs further validation.

What you'll be working on

• Release pipelines covering the full ML training and delivery lifecycle.
• Automated checks and tooling that identify issues earlier in development.
• Reliable evaluation methods for assessing model changes and release readiness.
• CI/CD workflows that streamline model integration and delivery.
• Monitoring and observability that improve confidence in production releases.
• Engineering standards and operational processes that enable teams to deliver high-quality ML systems at scale.

You should apply if

• You have significant software integration and release experience, including branching strategies, release cadences, and configuration management.
• You understand ML training, model lifecycles, and the infrastructure required to deliver models reliably.
• You can review someone else's model, architecture, or code changes and challenge decisions that do not align with their stated intent.
• You have experience with ML tooling and technologies such as PyTorch, TensorRT, model registries, quantisation, or model deployment.
• You are comfortable working with CI/CD systems and GitHub Actions.
• You take ownership of ambiguous, cross-team problems and prefer fixing underlying processes rather than repeatedly patching individual releases.
• You combine a strong quality mindset with the judgement to recognise when speed genuinely matters.
• You communicate clearly and collaborate effectively across research, engineering, platform, evaluation, and product teams.

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 worki