Mentor others and contribute to strong machine-learning and engineering practices.
🧩 WHAT YOU’LL BE WORKING ON
Transformer-based, multimodal, and vision-language models for detection, segmentation, classification, and scene understanding.
Offline models that use higher compute budgets, larger capacity, and bidirectional temporal context.
Automated benchmarks that assess coverage, mine rare events, and measure driving behaviour.
Fleet-scale camera, lidar, and simulation datasets.
Evidence used in model-development decisions, validation pipelines, customer deliverables, and safety cases.
🙌 YOU SHOULD APPLY IF
You have 4+ years in ML engineering and have trained and shipped deep-learning models in production.
You have hands-on experience with modern computer-vision, transformer, multimodal, or VLM architectures.
You have adapted or fine-tuned large pretrained or foundation models and understand data, loss, and representation trade-offs.
You are proficient in Python and PyTorch or a similar framework and comfortable with large-scale training.
You can take ambiguous modelling problems from scoping to a working, measurable solution.
Experience in 3D scene understanding, offline modelling, auto-labelling, temporal or world models, autonomous vehicles, robotics, or distributed training is valuable.
🌱 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.
Our ambition is to make autonomy universal. Wayve’s mapless and hardware-agnostic AI platform integrates with global OEM partners, enabling continuous software evolution from L2+ through to L4.
HOW WE WORK 💻 — LOCATIONS & FLEXIBLE WORKING
This role is based in Sunnyvale. We operate a hybrid model that combines in-person collaboration with focused time working remotely.
🔍 THE INTERVIEW PROCESS
Initial call / recruiter screen (25 min)
Competency interview (HM Screen; 60 min)
Deep-dive technical interviews (Applied ML, System Design, Programming; 3 hours)
Final interview focused on mission and values alignment (60 min)
We’ll always explain the format and work around your availability.
WHAT’S IN IT FOR YOU (LOCATION DEPENDENT)
💰 Salaries benchmarked against the market annually
📈 Meaningful equity
✈️ Relocation support and visa sponsorship where applicable
✅ Hybrid working and access to vehicle workshops and labs
📚 Learning and development support
🩺 Comprehensive location-dependent health, family, retirement, and wellbeing benefits
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.
