AI-powered general-purpose robot control systems and perception
Sanctuary builds AI control and perception systems for general-purpose robots, with a tech stack split between ML infrastructure (PyTorch, TensorFlow, JAX, CUDA) and full-stack web/cloud tooling (Python, TypeScript, React, Kubernetes, AWS/Azure/GCP). The engineering-heavy hiring profile (9 of 10 open roles) concentrated in senior and lead levels signals they're scaling hardware validation, manufacturing readiness, and ML deployment to production — pain points that dominate their active project list. Founded by veterans from D-Wave and Kindred, the org is tackling the hard problems of safety certification, actuation, and robotic hand development.
Sanctuary creates software and hardware systems that enable general-purpose robots to operate with human-like intelligence and safety. The company is based in Vancouver and employs 51–200 people, all hiring in Canada. Their current engineering focus spans robotics middleware (ROS 2), mechanical design tools (SolidWorks, Fusion 360, Mastercam, Onshape), ML pipelines for robot learning, and actuation and gripper subsystems. Active work includes safety compliance methodologies, validation frameworks, and a manufacturing readiness program — reflecting a transition from prototype development toward production-scale deployment. The team draws on deep experience in quantum computing, reinforcement learning in robotics, and science commercialization.
Python, TypeScript, React, PostgreSQL, PyTorch, TensorFlow, JAX, ROS 2, Docker, Kubernetes, AWS, Azure, GCP. Design tools: SolidWorks, Fusion 360, Mastercam, Onshape. No active tech replacements or new adopts tracked.
Safety compliance frameworks, manufacturing readiness, robotic hand and actuation development, ML pipeline and model deployment for robots, and perception systems. Pain points center on scaling hardware production and deploying ML models to robots in the field.
Sanctuary AI's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.