Staff Machine Learning Scientist/Engineer
Core
Building foundation models for general-purpose robots that learn from large-scale video, language, and robot-interaction data to perceive, reason, and act in the physical world.
Role type
Staff Machine Learning Scientist/Engineer (Founding Member)
Builds
Foundation-model learning stack for robotics including novel architectures, pre-training objectives, and scalable training systems
Domain
Robotics + Multimodal Foundation Models
Deliverable
production ML models
Required skills
Multimodal foundation models, scalable multi-node training, rigorous experimental design, translating research to working systems, distributed training pipelines, robotics data curation
Preferred skills
PhD in CS/ML/Robotics, industry experience in embodied AI, real robot/policy learning experience, large-scale video data expertise
Technologies
Modern ML frameworks, distributed training infrastructure
Responsibilities
Research and develop model architectures and learning objectives for robot foundation models; Develop scalable self-supervised and generative pre-training methods using web and robot-interaction data; Develop post-training approaches including imitation learning and reinforcement learning; Curate and evaluate large-scale robotics datasets; Build and use distributed training pipelines for large multimodal models; Collaborate with robotics and hardware teams to connect model progress to real-world performance; Communicate research findings internally and externally
Seniority
Staff, hands-on IC with strategy & mentorship