**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!
About the Science Team
The Wayve Labs team is a global group of leading scientists and engineers advancing the frontiers of autonomous driving through Embodied AI. We do this by unlocking breakthrough capabilities through cutting-edge research, enabling rapid integration of new technologies into production and disrupting ourselves, before someone else does.
The Role
We’re looking for Applied Scientists to join Wayve’s Science team and help build the next generation of AI systems for autonomous driving. You’ll work at the intersection of machine learning, simulation, robotics, and real-world deployment, contributing to core innovations that push the boundaries of what embodied AI can do.
Key Responsibilities
- Design and train large-scale embodied foundation models, advancing architectures in attention, mixture-of-experts, and distributed training.
- Develop world models and planners (e.g., diffusion, transformer-based, or hybrid generative approaches) to simulate diverse and temporally consistent driving environments.
- Innovate in reinforcement learning and reward modeling, building safe, efficient, and scalable reward frameworks integrated with real-world and synthetic data.
- Conduct empirical research on scaling laws, generalisation, and synthetic-to-real transfer for autonomous systems.
- Define benchmarks and metrics for long-horizon prediction, scene fidelity, planner integration, and driving performance.
What You’ll Bring
Must-haves:
- PhD, Master’s degree, or equivalent experience in Machine Learning, Computer Vision, Robotics, or related fields
- Applicants should have a minimum of 4 years’ experience in applied ML research or engineering. We are hiring for this level and above, so candidates with deeper expertise are encouraged to apply.
- Deep expertise in one or more of the following:
- Strong programming skills in Python and experience with PyTorch or equivalent ML frameworks
- Track record of publishing at top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL)
- Strong problem-solving ability, collaboration mindset, and ability to thrive in a fast-paced, interdisciplinary team
Nice-to-haves:
- Experience in autonomous driving, robotics, or simulation
- Familiarity with training at scale (e.g., FSDP, DeepSpeed, JAX)
- Knowledge of synthetic-to-real transfer or data-efficient learning
- Contributions to open-source ML tools or research infrastructure
Why Join Us
- Shape the future of embodied AI and next-generation autonomy
- Collaborate with world-class researchers, engineers, and builders
- Access massive real-world driving datasets, powerful compute, and production deployment pathways
- High-trust, high-autonomy culture that rewards bold ideas and deep thinking
- Publish, open-source, and contribute to the global AI research community
**What we offer you **
- Attractive compensation with salary and equity
- Immersion in a team of world-class researchers, engineers and entrepreneurs
- A unique position to shape the future of autonomy and tackle the biggest challenge of our time
- Bespoke learning and development opportunities
- Relocation support with visa sponsorship
- Flexible working hours - we trust you to do your job well, at times that suit you and your time
- Benefits such as an onsite chef, workplace nursery scheme, private health insurance, therapy, daily yoga, onsite bar, large social budgets, unlimited L&D requests, enhanced parental leave, and more!
This is a full-time role based in our office in Sunnyvale. 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.
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
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.