Applied Scientist, Controllable GAIA

Wayve
London, United Kingdom
Last month
Posted
11 Mar 2026 (Last month)

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.

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

Science 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 Science focusing on unlocking disruptive innovation that solves self-driving. We believe the next leap in autonomy won’t come from collecting endless real-world miles — it will come fromsimulating the world with unprecedented fidelity and generalisation. That’s whereGAIA, our generative world model, comes in.

As an Applied Scientist on the Science team, you’ll play a central role in developing the next generation of GAIA. Thesecontrollable world models will roll out diverse, photoreal, and physics-aware futures across multiple sensors (camera, radar, LiDAR), powering faster training, broader testing, and scalable deployment — even in places and situations we’ve never driven before.

GAIA-2 added multi-camera consistency, fine-grained control, and richer geographic diversity, enabling us to stress-test autonomy at scale. The next generation must go further:thousands of real-time rollouts per second, closed-loop interactivity with agents, and compute efficiency that makes training and deployment practical.

You’ll work at the intersection of generative modeling, simulation, and reinforcement learning, tackling questions like:

  • How can we deploy AVs in a new geography without collecting any real-world data?
  • Can synthetic environments trained with GAIA fully replace physical testing and data collection?
  • How do we design controllable models that allow agents to play, explore, and learn safely?

Key responsibilities:

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

  • Inventnext-generation generative world models (diffusion, transformer, or hybrid) that deliver real-time, controllable rollouts.
    Architectcontrollable GAIA models where agents can step into the world, enabling reinforcement learning, planning, and safety evaluation.
  • Define robust metricsfor long-horizon coherence, physics fidelity, and planner integration; run ablations and scaling studies to understand trade-offs.
  • Ship impact by integrating models with fleet-scale training, sim-to-real evaluation, and on-vehicle deployment.
  • Mentor & influence:guide junior researchers, shape technical roadmaps, publish at top venues, and represent Wayve in the global research community.
  • Challenge assumptions:propose bold ideas, run disruptive experiments, and question conventional approaches..

About you

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

  • Expertise in ML research/engineering with a focus on generative video, world models.
  • Deep knowledge in diffusion & latent-video models
  • 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.

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.

For more information visit Careers at Wayve.

To learn more about what drives us, visit Values at Wayve


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.

Related Jobs

View all jobs

Applied Scientist, Agentic Automated Reasoning

Amazon London, United Kingdom
Permanent

Applied Scientist II, TTS on Device

Amazon Cambridge, United Kingdom
Permanent

Applied Scientist, AGI Information

Amazon Cambridge, United Kingdom
Permanent

Applied Scientist I

Entrust London, United Kingdom

2026 Applied Scientist Intern, Amazon University Talent Acquisition

Amazon London, United Kingdom
Permanent

Research Scientist (Applied LLMs), London

Isomorphic Labs London, United Kingdom

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.