Research Scientist: Pretraining

Generalist • San Francisco, CA

5d

About The Position

You will build the base intelligence layer for robotics. We train large-scale robot foundation models from massive multimodal datasets spanning video, proprioception, action traces, language, and more. You will design and run the core large-scale training efforts that give our models fundamentally new general capabilities across embodiments, tasks, and environments. You will “live and breathe” all forms of robot data.

Requirements

• Deep experience training large transformer or diffusion models at scale (for generative models e.g. including language models, audio models, or video models)
• Led or significantly contributed to multi-node, multi-GPU distributed training efforts
• Worked on scaling laws, optimization dynamics, and large-model failure modes
• Strong PyTorch fundamentals and comfort debugging at every layer of the stack
• Care about both empirical rigor and raw iteration speed
• Excited about building general-purpose robot intelligence from first principles

Responsibilities

• Designing and executing large-scale pretraining runs for robot foundation models (transformer- and diffusion-based architectures)
• Defining model architectures, objectives, and training curricula across multimodal robotic data (vision, action, state, language)
• Developing scalable data mixtures and sampling strategies across petabyte-scale datasets
• Guiding data collection operations towards new directions, as well as sourcing new datasets
• Running ablations to understand scaling laws, data quality effects, and architecture tradeoffs
• Collaborating closely with ML Infra and Systems to push cluster utilization, throughput, and reliability
• Turning raw robotic interaction data into generalizable model capabilities

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed