Principal Machine Learning Engineer GAIA

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.

🛠️ About our Simulation Teams

You'll be joining the Simulation team (Simulation Evaluation & Validation), working on Gaia — Wayve's world model. Gaia is trained on large-scale driving video to predict future frames from past context, functioning as a simulator that generates synthetic scenarios and operates in closed loop with the driving model itself. The team partners closely with Research, Applications, Core Simulation Engineering, and Cloud/Infrastructure to turn model improvements into measurable downstream impact on the driving stack.

🧠 Your day-to-day

- Own and lead parts of large-scale training for Gaia (language- or video-style training at scale), from experimentation through productionised training runs.

- Contribute to and influence model architecture decisions — not just applying existing models.

- Partner across sub-teams: Research (model development), Applications (adapting models to use cases), Core Simulation Engineering, and Cloud/Infrastructure.

- Translate product and evaluation needs into model improvements (e.g. better long-horizon prediction, scenario generation quality, failure-case coverage).

- Mentor and set technical direction, raising the engineering and research quality bar across the team.

🧩 What you’ll be working on

- Leading and executing Gaia's post-training and closed-loop pipeline — fine-tuning and aligning the world model through post-training experimentation and targeted data curation.

- Pushing Gaia's autoregressive generation towards longer, more stable rollouts, and making the model deployment-ready (inference time and reliability included).

- Contributing to broader model architecture and training-strategy decisions where they intersect with pre- and post-training and the application layer.

- Partnering closely with research, applications, simulation engineering, and cloud/infrastructure teams to translate post-training improvements into measurable downstream impact.

- Providing technical leadership through mentorship, review, and setting high engineering/research standards.

🙌 You should apply if

Essential:

- You have hands-on experience post-training/fine-tuning large-scale models (language, video, or other foundation models).

- You have experience with world models, autoregressive generation, and long-horizon generation.

- You have experience with diffusion/flow models and a solid understanding of 3D vision.

- You have a strong understanding of model architecture and can contribute meaningfully to architectural/training decisions.

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

- You have 5+ years of relevant industry experience (advanced degrees are valued, but depth of applied experience matters more).

Desirable:

- Experience with inference optimisation or deploying large models under latency/compute constraints.

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

- Proven technical leadership — tech lead ownership, mentoring, or setting direction across an area.

🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement.

More about Wayve:

🚀 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines.

Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility.

How we work 💻- Locations & Flexible Working:

Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives.

🔍 The Interview Process:

Our process is clear and respectful of your time:

- Initial call / recruiter screen (30 mins)

- Competency Interviews (Programming/Pytorch debugging and hiring manager interview; 2 hours total)

- Deep-dive technical interviews (Systems & domain-specific interviews; 3 hours total)

- Final interview: Mission & values alignment (45 mins).

We’ll always explain the format and work around your availability.

What’s in it for you (Location dependant):

💰 Salaries benchmarked against the market annually 📈 Meaningful equity, sharing in the ownership and long term success of Wayve ✈️ Relocation support and visa sponsorship where applicable ✅ Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs 📚 Learning and development budgets with support for training, conferences and growth 🩺 Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more

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.

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. https://wayve.ai/careers/ To learn more about what drives us, visit Values at Wayve https://wayve.ai/careers/

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.