At Mind Robotics, we’re building generalized physical AI—robotic systems capable of dexterous, adaptive, and reasoning-intensive work in real-world industrial environments. Our models sit at the core of this effort, bridging cutting-edge foundation model techniques with real-world robotic execution.
We’re looking for a Research & Modeling Engineer to build and train the core models that power our systems, and ensure they perform reliably on real robots in production environments.
Design and run large-scale training pipelines for multimodal / VLA systems
Own the full loop: data training evaluation deployment on real robots
Develop scalable infrastructure for data ingestion, training, and iteration
Translate model outputs into reliable, high-performance robotic actions
Work hands-on with robots to debug, iterate, and improve behavior
Define data strategy (quality, scale, diversity) and evaluation frameworks
Continuously improve performance across real-world tasks and environments
Built and trained large-scale models (LLMs, VLMs, or robotics foundation models)
Deep understanding of modern ML, training dynamics, and optimization at scale
Experience with distributed systems and data pipelines for large-scale training
Comfortable operating end-to-end: from data model real-world deployment (incl. robots)
Domain strength in at least one: robotics, VLA systems, or training LLMs/VLMs from scratch
Strong Python skills
Experience with dexterous manipulation or complex robotic tasks
Experience deploying models in real-world, production environments
| Location | Palo Alto, California |