We believe general-purpose, generally-intelligent robots will be built in our lifetimes. Robots will work in our factories, move our goods, walk on our streets and eventually be in our homes. To build that future, research and deployment must work in lockstep: real-world operation must make the technology better, and better technology must make deployment easier. We're looking for the thinkers, builders, and researchers who want to be part of that loop.
Founded by MIT alumni and backed by over $40M from leading AI and robotics investors, we deploy real robotic systems directly into the facilities that power the physical economy. We don't just build robots — we build them, ship them, and keep them running.
We're looking for a hands-on Production Engineer (Electrical Test) to build and own the electrical test systems that ensure every robot we ship meets our standards for quality, reliability, and performance.
This role reports to the Head of Manufacturing and Supply Chain, with a dotted line to Hardware Engineering.
The goal is simple: build a system that lets us deliver high-quality robots at scale and at the lowest practical cost.
You'll work directly with Manufacturing, Hardware Engineering, Firmware, Quality, and Supply Chain to turn electrical designs into robust, repeatable production systems. This is a floor-first role — you'll spend real time at the bench and on the line, not behind a desk.
Build the test system
Make the data useful
Find root cause
Scale it
You like to build things and figure out why things fail.
You don't stop at "the board is bad." You want to know what failed, why it failed, and how we prevent it from happening again.
You can take an ambiguous problem, build the test, collect the data, find the root cause, and push the solution forward.
You understand that a great robot design isn't finished until we can build it, test it, troubleshoot it, and scale it.
Most importantly, you are creative, hands-on, and can figure out pretty much anything.
Tutor was founded to build the intelligence that lets machines see, learn, and act alongside people in the most complex, real-world production environments. Our teams work at the edge of AI, robotics, and operations to embody robotic systems with humans’ intuitive understanding of the physical world and how to interact with it.
