Robotics Foundation AI Scientist

Generalist AI, Inc.; Boston (MA); On-site; USD 150,000 - 230,000; Full time

Job summary

Generalist AI, Inc. seeks a Senior/Staff ML Engineer to build the base intelligence layer for robotics. You will train large-scale robot foundation models from vast multimodal data, spanning video, proprioception, action traces, language, and more.

You will design and run core training efforts that enable new capabilities across embodiments and environments. If you have worked on pretraining large-scale ML systems or generative foundation models (multimodal, language, audio), this role may be

Qualifications

• Experience with large-scale ML systems and robotics data.
• Proven ability to run multi-node, multi-GPU training.
• Understanding of scaling laws and model reliability.

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 toward 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 optimize cluster utilization and reliability
• Turning raw robotic interaction data into generalizable model capabilities
• You will live and breathe all forms of robot data.

Skills

PyTorch fundamentals

Distributed training

Scaling laws

Data quality assessment

Empirical rigor

Robot foundation models

Debugging at stack level

Tools

PyTorch

Job description

Generalist AI, Inc. seeks a Senior/Staff ML Engineer to build the base intelligence layer for robotics. You will train large-scale robot foundation models from vast multimodal data, spanning video, proprioception, action traces, language, and more.

You will design and run core training efforts that enable new capabilities across embodiments and environments. If you have worked on pretraining large-scale ML systems or generative foundation models (multimodal, language, audio), this role may be