Applied Scientist, Wayve Labs
Tasks
- Advance reinforcement learning and reward modeling
- Conduct empirical research on scaling laws and generalisation
- Define evaluation frameworks and benchmarks
- Develop geometric foundation models for spatial understanding
- Develop world models and planners for simulation
- Enable cross embodiment robotics with multimodal foundation models
- Perform sim to real transfer research
Perks/Benefits
- Daily yoga
- Enhanced parental leave
- Flexible working hours
- Onsite bar
- Onsite chef
- Private health insurance
- Relocation support
- Therapy
- Unlimited L and D Requests
- Visa sponsorship
- Workplace nursery scheme
Skills/Tech-stack
Autoregressive models | Depth Estimation | Diffusion Models | Foundation Models | Human Feedback | Large Scale Training | Large-scale | Learning from Human Feedback | Machine Learning | Mixture of Experts | Multi-view Geometry | Offline Reinforcement Learning | PyTorch | Python | Reinforcement Learning | Reinforcement Learning from Human Feedback | Reward Modeling | SFM | SLAM | Sim-to-Real | Transformers
Education
Roles
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