Machine Learning Engineer GAIA

Wayve; Greater London; Hybrid; GBP 120,000 - 170,000; Full time

Benefits offered by this job

Equity participation

Relocation support

Hybrid work model

Learning & development budget

Job summary

Wayve ищет ведущего специалиста по обучению Gaia в рамках команды Simulation Evaluation & Validation. Вы будете заниматься крупномасштабным обучением, настройкой и улучшением мир-модели Gaia, а также координацией взаимодействий между исследованиями, применением и инженерными группами.

Ваша роль включает руководство пост-тренировкой, оптимизацию инференса и генерацию сценариев, направление архитектурных и обучающих стратегий, а также менторство команды и обеспечение высокого уровня инженерии и

Qualifications

• У вас есть практический опыт обучения или финетюнинга крупномасштабных моделей (язык, видео или другие базовые модели).
• Есть опыт работы с миром-моделями, авто-регрессивной генерацией и долгосрочной генерацией.
• Опыт с диффузионными/flow моделями и базовое понимание 3D-визии.
• Сильное понимание архитектуры моделей и вклад в архитектурные/обучающие решения.
• Сильные инженерные навыки на стеке ML (PyTorch), отладка и надежная разработка.
• Опыт не менее 5 лет в индустрии (приветствуется академическая степень, но важнее глубина опыта).
• Опыт в инференс-оптимизации или развёртывании крупных моделей с учётом задержек и вычислений.
• Опыт улучшения data/training pipelines и работы в инфраструктурных ограничениях (распределённое обучение, производительность, надежность).
• Доказанное техническое лидерство — Tech Lead, наставничество, или направление в рамках области.

Responsibilities

• Вести масштабные этапы обучения Gaia (на базе текста/изображений) от экспериментов до продакшн-обработки.
• Вносить архитектурные решения и развивать архитектуру моделей.
• Сотрудничать с Research, Applications, Core Simulation Engineering и Cloud/Infrastructure.
• Переводить потребности продукта и оценки в улучшения моделей (долгосрочное прогнозирование, качество генерации сценариев).
• Менторство и формирование технологических стандартов команды.
• Руководить пост-тренингом Gaia и закрытым контурами: дообучение, настройка моделей, отбор данных.

Skills

Hands-on ML

World models

Autoregressive generation

Diffusion models

3D vision

PyTorch

Distributed training

Leadership

Tools

PyTorch

CUDA

Git

Job description

Описание

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. 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.

Задачи

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. 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.

Требования

• 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).
• 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.

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. For more information visit Careers at Wayve. To learn more about what drives us, visit Values at Wayve.

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.

Условия

• 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.

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.