Staff ML Engineer Gaia

Wayve; London (KY); Hybrid; USD 159,000 - 238,000; Full time

Benefits offered by this job

Hybrid work policy

Office in London

Job summary

Wayve in London is seeking a Staff ML Engineer for Gaia to own training of frontier-scale video foundation models and help shape Gaia’s next version in a fast-paced, results-driven environment.

You will lead large-scale training runs, contribute to architecture decisions, collaborate across research, applications, and infrastructure, and mentor engineers while upholding high engineering standards in a hybrid London office.

Qualifications

• Experience training large-scale models (language, video, or other foundation models) with ownership of training at scale.
• Strong understanding of model architecture and ability to influence training decisions.
• Hands-on engineering with modern ML stacks, debugging and reliable development.

Responsibilities

• Lead and execute large-scale training runs for video foundation models from design to production.
• Contribute to model architecture and training strategy with principled approaches.
• Improve world-model capabilities for synthetic scenario generation and evaluation.
• Collaborate with research, applications, simulation, and cloud teams to deliver end-to-end impact.
• Provide technical leadership through mentorship and setting high standards (Senior/Staff scope).

Skills

Large-scale model training

PyTorch / ML frameworks

Distributed training

Architectural thinking

Mentoring / leadership

Education

Advanced degree (PhD/MS)

Tools

PyTorch

TensorFlow

Cloud platforms (AWS/GCP)

ML tooling (MLflow/W&B)

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.

The role

Gaia is Wayve’s video world model: trained on large-scale driving video, it predicts future frames from past context—functioning as a simulator that helps generate synthetic scenarios, including rare or safety-critical events. As a Staff ML Engineer on Gaia, you’ll own and drive work on training and improving frontier-scale models trained in-house. This is a high-impact role with the opportunity to tech‑lead a key area and help shape the next version of Gaia in a fast‑paced, results‑focused environment.

Key responsibilities:

• Lead and execute large-scale training runs for video (or adjacent) foundation models, from experimental design through production-grade execution

• Contribute to model architecture and training strategy, using first-principles understanding rather than “off-the-shelf” application

• Improve world-model capabilities that enable synthetic scenario generation and downstream evaluation/training of the driving model

• Partner closely with research, applications, simulation engineering, and cloud/infrastructure teams to deliver end-to-end impact

• Provide technical leadership through mentorship, review, and setting high engineering/research standards (Senior/Staff scope)

About you

In order to set you up for success as a Staff ML Engineer (Gaia) at Wayve, we’re looking for the following skills and experience.

Essential

• In-depth experience training large-scale models (language, video, or other foundation models), including ownership of training at scale

• Strong understanding of model architecture and the ability to contribute meaningfully to architectural/training decisions

• Strong hands‑on engineering skills with modern ML stacks (e.g., PyTorch), including debugging and performance/reliability-minded development

• Relevant industry experience (typically 4–5+ years); advanced degrees are valued, but depth of applied experience is important

Desirable

• Direct experience with world models, video generation, or long‑horizon prediction

• Experience improving data/training pipelines and working across infrastructure constraints (distributed training, efficiency, reliability)

• Proven technical leadership (tech lead ownership, mentoring, setting direction across an area)

This is a full‑time role based in our office in London. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.

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.