Machine Learning Engineer (Closed Loop)

Wayve
London, United Kingdom

Who this role is best for

Strong fit for ML engineers with generative video and world model experience who can work in a hybrid office environment and thrive in a fast-paced, interdisciplinary team setting.

Best fit for

  • Candidates with generative video modeling expertise and a track record in AI research for autonomous vehicles
    — “4+ years of experience in ML research/engineering with a focus on generative video, world models.
  • Individuals who have optimized high-dimensional models for real-time performance and scalability
    — “Optimise end-to-end performance – from latent compression to context pruning your aim is to reduce inference latency by orders of magnitude.
  • Professionals who can lead technical innovation and mentor junior researchers in a high-autonomy team
    — “Mentor & influence: guide junior researchers, shape technical road-maps, publish at top venues and represent Wayve in the community.

Things to consider

  • Hybrid office attendance is expected, with core working hours in place
    — “We operate core working hours so you can determine the schedule that works best for you and your team.
  • Candidates must be prepared to integrate models into real-world AV systems and measure sim-to-real gaps
    — “Ship impact: integrate your models into closed-loop training and evaluation, and measure the sim-to-real gap against on-road driving-model results.

How to stand out

  • Highlight experience with diffusion models and real-time performance optimization in your resume and interviews
    — “Invent next-generation, efficient generative world-models (diffusion, transformer or hybrid) that deliver real-time roll-outs
  • Showcase prior work on synthetic-to-real transfer and multi-modal modeling in your portfolio or project descriptions
    — “Experience working with synthetic-to-real transfer.
  • Emphasize contributions to open-source tooling or research publications related to autonomous systems
    — “Strong publication record or contributions to open-source ML tooling.
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · TeamLevel · Senior

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

What success looks like

  • developed next-generation world models
  • optimized end-to-end performance
  • integrated models into closed-loop systems
Typical background
PhD in Computer Science, Electrical Engineering, or related fieldexperience in machine learning research

Skills & requirements

Required

Machine LearningGenerative SimulationClosed Loop SystemsAI Software DevelopmentAutonomous Driving

Preferred

Diffusion ModelsTransformer ModelsReinforcement LearningPlanning Algorithms

Stack & domain

Machine LearningSimulationAutonomous DrivingAIPlannersWorld ModelsDiffusionTransformerReinforcement LearningPlanningSafety EvaluationLatent CompressionContext PruningMetricsAblationsScaling StudiesGAIATeamworkProblem-solvingLeadershipCommunicationCollaborationInnovation

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

Generative simulation is the team that is advancing our end-to-end autonomous driving research. The team’s mission is to accelerate our journey to AV2.0 and ensure the future success of Wayve by incubating and investing in new ideas that have the potential to become game-changing technological advances for the company.

Where you’ll have impact:

This role would sit within Simulation focusing on unlocking disruptive innovation that solves self-driving. We believe the next leap in autonomy comes from a world model that is faithful enough, and fast enough, to train and evaluate driving models in closed loop — not only to replay logs.

As a Machine Learning Engineer in the Simulation team, you’ll play a key role in developing next-generation world models and planners that can simulate complex, diverse, and temporally consistent driving environments. These generative simulation models (like GAIA) will power faster training, broader testing, and scalable deployment—even in areas and scenarios we’ve never driven in before.

As we push toward the next generation of GAIA, efficiency and interactivity become a great focus area: models must run thousands of roll-outs per second, support closed-loop agent interaction and fit within practical compute budgets. This role will lead that leap.

You’ll work at the intersection of machine learning research, multi-modal modeling, and real-world deployment tackling questions like:

How can we deploy AVs in a new geography without collecting any real-world data?

Can synthetically generated environments fully replace physical testing and data collection?

Key responsibilities

You will be a senior technical contributor inside Simulation, the team that incubates breakthrough ideas for Wayve. Your mandate:

Invent next-generation, efficient generative world-models (diffusion, transformer or hybrid) that deliver real-time roll-outs and controllable scene editing.

Architect interactive world models where agents (or humans) can step the model, enabling reinforcement learning, planning and safety evaluation loops.

Optimise end-to-end performance – from latent compression to context pruning your aim is to reduce inference latency by orders of magnitude.

Define robust metrics for long-horizon coherence, physics fidelity and planner integration; run ablations and scaling studies to understand trade-offs.

Ship impact: integrate your models into closed-loop training and evaluation, and measure the sim-to-real gap against on-road driving-model results.

Mentor & influence: guide junior researchers, shape technical road-maps, publish at top venues and represent Wayve in the community

Challenge assumptions and drive innovation: propose bold ideas, conduct ablation studies, and question conventional approaches to training and evaluation.

About you

In order to set you up for success at  Wayve, we’re looking for the following skills and experience.

4+ years of experience in ML research/engineering with a focus on generative video, world models.

Deep knowledge in diffusion & latent-video models; track record of improving sampling efficiency or model throughput

Experience working with high-dimensional temporal or spatial-temporal data (e.g., video, multi-sensor fusion).

Strong Python and PyTorch engineering fundamentals, and experience building research-grade production tools.

Strong publication record or contributions to open-source ML tooling.

Ability to work collaboratively in a fast-paced, innovative, interdisciplinary team environment.

Desirable

Experience in AVs, robotics, simulation, or other embodied AI domains.

Experience working with synthetic-to-real transfer.

Why Join Us

Work on transformative technology with real-world impact on mobility, safety, and AI.

Access massive driving datasets, cutting-edge infrastructure, and world-class research talent.

Be part of a high-trust, high-autonomy team that values creativity, experimentation, and deep thinking.

Publish, share, and shape the future of generative AI for autonomy.

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.   We operate core working hours so you can determine the schedule that works best for you and your team.  

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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