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9 hours ago Lead London, UK Hybrid Full Time Ai Jobs by Wayve
Wayve
Wayve is a London-headquartered embodied-AI company developing and licensing mapless, vehicle-agnostic driving software for assisted, automated, and robotaxi applications.
Location: London, United Kingdom
Funding history:
- Employee tender offer
- Series D extension ($60M)
- Series D ($1.2B)
Investors:
- Rosemary Leith
- Uber
- Nvidia
- Baillie Gifford
- SoftBank Vision Fund 2
About Wayve
Wayve Technologies Ltd. develops the Wayve AI Driver, an end-to-end, data-trained software platform that runs on onboard vehicle compute and native sensors. It is designed for OEM integration across L1 driver assistance through L4 automated driving, without HD maps.
Skills
Deepspeed, Foundation Model, Fsdp, Jax, Machine Learning, Python, Pytorch, Reinforcement Learning, Reward Modeling, Robotics, Simulation, Slam, Spatial Ai, World Model
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Candidate Availability
Location: London
Type: Hybrid
About The Role
You will develop world models, planners, reinforcement-learning and reward-modeling systems for realistic simulation. You will advance geometric foundation models and multimodal robotics learning, research scaling and sim-to-real transfer, and define evaluation frameworks for long-horizon prediction and driving performance.
Requirements
- 3+ years of experience developing and deploying machine-learning systems in real-world or production settings
- PhD, Master's degree, or equivalent experience in machine learning, computer vision, robotics, or a related field
- Expertise in embodied AI areas such as foundation models, generative world modeling, reinforcement learning, or spatial AI
- Publication record at top-tier conferences
- Python and PyTorch experience
- Experience with large-scale datasets and evaluation
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Responsibilities
- Develop world models and planners for realistic, consistent simulation
- Advance reinforcement learning and reward modeling across real and synthetic data
- Develop geometric foundation models for 3D spatial understanding
- Enable cross-embodiment robotics using multimodal foundation models
- Conduct research on scaling laws, generalisation, and sim-to-real transfer
- Define and evolve evaluation frameworks and benchmarks
Benefits
- Equity
- Relocation support with visa sponsorship
- Flexible working hours
- Onsite chef
- Workplace nursery scheme
- Private health insurance
- Therapy
- Daily yoga
- Onsite bar
- Large social budgets
- Enhanced parental leave
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