Staff Research Scientist, Reinforce Learning

Requirements

• 3+ years of experience developing and deploying ML systems in real-world or production settings
• PhD, Master’s degree, or equivalent experience in Machine Learning, Computer Vision, Robotics, or a related field
• Deep expertise in one or more core Embodied AI areas, such as:
  • Foundation models (e.g., transformers, MoE, large-scale training)
  • Generative world modeling (e.g., diffusion, autoregressive, hybrid approaches)
  • Reinforcement learning (e.g., offline RL, RLHF, reward modeling)
  • Spatial AI (e.g., SLAM/SfM, depth estimation, multi-view geometry with multimodal sensors)
• Track record of publications at top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL)
• Strong programming skills in Python, with experience using frameworks such as PyTorch
• A data-centric mindset, with experience working on large-scale datasets and evaluation
• Strong problem-solving ability and the ability to collaborate effectively in interdisciplinary teams

Nice to Haves

• Experience in autonomous driving, robotics, or simulation systems
• Familiarity with large-scale training (e.g., FSDP, DeepSpeed, JAX)
• Experience with sim-to-real transfer or data-efficient learning
• Contributions to open-source ML tools or research infrastructure

What You'll Be Doing

• Develop World Models and Planners (e.g., diffusion-based, autoregressive, or hybrid approaches) for realistic and consistent simulation
• Advance Reinforcement Learning and Reward Modeling, building scalable and safe learning frameworks across real and synthetic data
• Develop Geometric Foundation Models for 3D spatial understanding in dynamic, real-world environments.
• Enable Cross-Embodiment Robotics, leveraging the power of multimodal foundation models to accelerate robotic learning on diverse platforms.
• Conduct empirical research on Scaling laws, Generalisation, and Sim-to-real transfer
• Define and evolve Evaluation Frameworks and Benchmarks for long-horizon prediction, scene fidelity, and driving performance

Perks and Benefits

• 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!