Research Member of Technical Staff- Efficient Modeling

Highlights

• Make foundation world models faster and deployable on real robot hardware.
• Close the gap between research-scale models and real-time robot operation.
• Efficiency improvements benefit every model the team trains and deploys.

What they offer

• Equity

Ideal candidate

A research-minded engineer obsessed with squeezing frontier models onto real hardware. You love principled experimentation and seeing efficiency work unlock real-time robots.

Requirements

• Strong understanding of model compression and efficient architectures for large models
• Hands-on experience with quantization, distillation, or pruning for transformers or large neural networks
• Deep knowledge of efficiency opportunities in modern architectures
• Proficiency with PyTorch and hardware-aware optimization (CUDA, TensorRT, or similar)
• Ability to run principled experiments on capability-efficiency tradeoffs