Embodied AI Scientist — Autonomous Driving & Robotics

OpenDigital Limited; Greater London; Hybrid; GBP 90,000 - 160,000; Full time

Benefits offered by this job

Relocation support with visa

Flexible working hours

Onsite chef

Private health insurance

Daily yoga

Job summary

Wayve Labs in London is seeking Research Scientists to advance embodied AI for autonomous driving and robotics. You will work at the intersection of machine learning, simulation, robotics, and real-world deployment to push multi-year breakthroughs.

Join a high-conviction team focusing on world models, spatial understanding, scalable decision-making, and cross-embodiment learning across diverse platforms. We encourage collaboration and impactful research outcomes.

Qualifications

• 3+ years developing and deploying ML systems in real-world settings.
• Advanced degree in ML/CS/Robotics or equivalent experience.
• Deep expertise in Embodied AI areas and foundation models.
• Strong programming in Python with PyTorch experience.

Responsibilities

• Develop World Models and Planners for realistic simulation.
• Advance RL and reward modeling across real and synthetic data.
• Develop Geometric Foundation Models for 3D spatial understanding.
• Enable Cross-Embodiment Robotics with multimodal inputs.
• Conduct empirical research on scaling laws and sim-to-real transfer.
• Define evaluation frameworks and benchmarks for long-horizon tasks.

Skills

3+ years ML systems

PhD or MSc in ML/CS/Robotics

Foundation models

Generative world modeling

Reinforcement learning

Spatial AI

Publications in top conferences

Python

PyTorch

Collaborative research

Education

PhD, Master’s degree in ML/CS/Robotics

Tools

PyTorch

DeepSpeed

JAX

Job description

Wayve Labs in London is seeking Research Scientists to advance embodied AI for autonomous driving and robotics. You will work at the intersection of machine learning, simulation, robotics, and real-world deployment to push multi-year breakthroughs.

Join a high-conviction team focusing on world models, spatial understanding, scalable decision-making, and cross-embodiment learning across diverse platforms. We encourage collaboration and impactful research outcomes.