Do you believe the path to general-purpose physical AI runs through noisy, real-world factory deployments?
Are you excited by the challenge of turning the classical robotic stacks into the foundational training data for physical AI?
Do you want to bridge the gap between world-class ML research and industrial-scale robotic execution?

If your answers are yes, we should talk.

At Nomagic, we are executing a humble pivot for general-purpose physical AI. We believe that physical AI is fundamentally a knowledge transfer problem - we are leveraging the "internet data" of robotics - massive deployment logs from real systems operating in production environments -  to bootstrap our efforts. We are looking for Research Engineers who will help us to build, train, and deploy foundational models that bring our fleet from a classical control stack to generalized AI mastery.