Machine Learning Engineer (Closed Loop)

Lindus Health; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid working policy

London office

Job summary

Wayve in London is seeking a senior Machine Learning Engineer for the Simulation team. The role focuses on building next‑generation world models and planners that can simulate complex driving environments with real-time roll‑outs and controllable scene editing.

You’ll push toward GAIA‑like models, optimizing efficiency to run thousands of roll-outs per second and enabling closed‑loop agent interaction within practical compute budgets.

Qualifications

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

Responsibilities

• Invent next-generation, efficient generative world-models (diffusion, transformer or hybrid) delivering real-time roll-outs.
• Architect interactive world models enabling reinforcement learning, planning and safety loops.
• Optimise end-to-end performance to reduce inference latency.
• Define robust metrics for long-horizon coherence and planner integration; run ablations.
• Ship models into closed-loop training and evaluation; measure sim-to-real gaps.
• Mentor junior researchers and shape technical roadmaps.

Skills

Python

PyTorch

Generative models

World models

Diffusion

Tools

PyTorch

Job description

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. 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.