Senior Robot Foundation Models Scientist

Generalist AI; San Mateo (CA); On-site; USD 210,000 - 270,000; Full time

Job summary

Generalist AI is seeking a senior ML engineer to build the base intelligence layer for robotics in the San Mateo area. You will lead pretraining for robot foundation models using multimodal data, and define architectures and curricula for scalable training across large datasets.

Collaboration with ML Infra and robotics teams will be essential as you push performance and reliability. The role emphasizes hands-on model development, rigorous experimentation, and accelerating progress toward

Qualifications

• Experience training large transformer or diffusion models at scale.
• Experience with multi-node, multi-GPU distributed training.
• Strong background in empirical rigor and model scaling.
• Proficient in debugging across ML stack.

Responsibilities

• Design and run large-scale pretraining runs for robot foundation models (transformer- and diffusion-based).
• Define model architectures, objectives, and training curricula across multimodal robotic data (vision, action, state, language).
• Develop scalable data mixtures and sampling strategies across petabyte-scale datasets.
• Guide data collection directions and sourcing of new datasets.
• Run ablations to study scaling laws, data quality effects, and architecture tradeoffs.
• Collaborate with ML Infra and Systems to push cluster utilization and reliability.
• Turn raw robotic interaction data into generalizable model capabilities.

Skills

Senior / Staff level ML Engineer

Transformer models

Diffusion models

Multi-node distributed training

PyTorch

Tools

PyTorch

GPU clusters

Job description

Generalist AI is seeking a senior ML engineer to build the base intelligence layer for robotics in the San Mateo area. You will lead pretraining for robot foundation models using multimodal data, and define architectures and curricula for scalable training across large datasets.

Collaboration with ML Infra and robotics teams will be essential as you push performance and reliability. The role emphasizes hands-on model development, rigorous experimentation, and accelerating progress toward