Robot Foundation Models Research Scientist

Generalist AI Inc.; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Generalist AI, Inc. is seeking a senior research-engineer to build the base intelligence layer for robotics.

You will train large-scale robot foundation models from diverse multimodal datasets and design core training runs that enable models to exhibit new capabilities across embodiments, tasks, and environments. If you have worked on pretraining large-scale ML systems or generative foundation models beyond robotics, this may be the role for you.

Qualifications

• Experience building large-scale ML systems.
• Experience with multi-node, multi-GPU distributed training.
• Familiarity with multimodal data (vision, language, action).
• Strong debugging and optimization skills in PyTorch.

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 and sourcing new datasets.
• Running ablations to understand scaling laws, data quality effects, and architecture tradeoffs.
• Collaborating with ML Infra and Systems to push cluster utilization, throughput, and reliability.
• Turning raw robotic interaction data into generalizable model capabilities.

Skills

Large-scale ML systems

Distributed training

Multimodal data

PyTorch fundamentals

Data throughput optimization

Tools

PyTorch

Job description

Generalist AI, Inc. is seeking a senior research-engineer to build the base intelligence layer for robotics.

You will train large-scale robot foundation models from diverse multimodal datasets and design core training runs that enable models to exhibit new capabilities across embodiments, tasks, and environments. If you have worked on pretraining large-scale ML systems or generative foundation models beyond robotics, this may be the role for you.