Staff ML Engineer, Gaia

Wayve
London, GB
On-siteCareer-pivot friendly

Who this role is best for

Aimed at mid-level ML engineers with experience in large-scale model training who thrive in a hybrid London office environment.

Best fit for

  • Engineers who have led large-scale model training from design to execution.
    — “Lead and execute large-scale training runs for video (or adjacent) foundation models
  • Candidates comfortable contributing to model architecture beyond standard applications.
    — “Contribute to model architecture and training strategy, using first-principles understanding
  • Individuals with a track record in video generation or long-horizon prediction.
    — “Direct experience with world models, video generation, or long-horizon prediction

Things to consider

  • Hybrid work policy requires regular in-office presence in London.
    — “This is a full-time role based in our office in London
  • Role involves close collaboration with multiple technical teams.
    — “Partner closely with research, applications, simulation engineering, and cloud/infrastructure teams

How to stand out

  • Highlight specific instances where you improved model training pipelines.
    — “Experience improving data/training pipelines and working across infrastructure constraints
  • Demonstrate technical leadership through examples of mentorship or direction-setting.
    — “Proven technical leadership (tech lead ownership, mentoring, setting direction across an area)
  • Showcase hands-on engineering skills with modern ML stacks like PyTorch.
    — “Strong hands-on engineering skills with modern ML stacks (e.g., PyTorch)
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Lead large-scale training runs
  • Contribute to model architecture
  • Improve world-model capabilities
  • Collaborate with cross-functional teams
  • Provide technical mentorship
Typical background
Machine Learning EngineerStaff ML Engineer

Skills & requirements

Required

Large-scale Model TrainingVideo Foundation ModelsModel ArchitectureTraining StrategyModern ML StacksDebuggingPerformance/reliability DevelopmentTechnical Leadership

Preferred

World ModelsVideo GenerationLong-horizon PredictionData/training PipelinesInfrastructure Constraints

Stack & domain

Embodied Ai TechnologyAdvanced Ai SoftwareFoundation ModelsVideo World ModelSynthetic Scenario GenerationModel ArchitectureTraining StrategyPyTorchDebuggingPerformance/reliability-minded DevelopmentLeadershipCommunicationProblem-solvingTeamworkAIMachine Learning

About the role

Original posting from Wayve

About us   

Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.

Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. 

In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.

At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  

Make Wayve the experience that defines your career!  

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.   

 

Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know.

We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.

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 

For US candidates only, please visit E-Verify Notice and Participation and Right to Work

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.

 

 

Source: Wayve careers

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