Senior Research Scientist

We’re partnering with a well-funded, frontier AI and robotics company building the intelligence layer for general-purpose robots
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This team is training large-scale, multimodal foundation models that enable robots to understand and interact with the physical world across tasks, environments, and embodiments. Their goal is ambitious: build models that generalise - not just perform.

They are looking for a senior-level research scientist to lead large-scale training efforts across massive robotic datasets and push the limits of embodied AI.

If you think in terms of scaling laws, data mixtures, architecture trade-offs, and cluster efficiency — this role is built for you.

Strong candidates will likely have:

• Deep experience training large transformer or diffusion models at scale
• (e.g., language models, generative video, audio, or other foundation models)
• Experience leading or contributing to multi-node, multi-GPU distributed training
• A strong understanding of scaling laws, optimisation behaviour, and large-model failure modes
• Excellent PyTorch fundamentals and comfort debugging across the stack
• A balance of empirical rigour and rapid experimentation
• Genuine interest in building general-purpose embodied intelligence

Experience in robotics is valuable but not required. Experience at the frontier model scale is.

This company sits at the intersection of: