We believe robots should be the next chapter in making physical labor safer and more affordable. But, nearly nine out of ten American factories and warehouses don’t have a single robot. Tutor Intelligence is changing that.

We build robots that go straight into real factories and warehouses, to do real work, with real impact. Our robot Cassie does back-breaking work, moving boxes, pallets, and bulk goods for family-owned manufacturers to some of the largest brands in the world. Our robot Sonny does handwork, using two arms to achieve human-like dexterity in picking and packing. Every robot learns on the job, and each one we deploy makes the next one more capable, more affordable, and faster to put to work.

Founded at MIT and headquartered in Watertown, MA, we do it all in-house: the robotics hardware, the machine learning, and the field deployment and service. We’re a team of researchers, engineers, technicians, operators, and sellers who love building things and solving hard problems.

Our mission is grand: robots everywhere, for the common good, raising the standard of living across North America, and then the world.

Whether you’re designing robots, closing deals, running deployments, or creating the processes that help us scale, your work doesn’t sit on a shelf. It shows up on real production floors, making physical work safer and more affordable.

Our team of 160+ is driven by curiosity and a genuine love of building. Everyone here takes real ownership, learns fast, and holds a high bar while having each other’s backs. If you love hard problems and creating things that didn’t exist before, you’ll fit right in.

Tutor Intelligence robots run production on customer floors across North America. The fleet is growing faster than the tools behind it.

This role exists to fix that by building. The job is to find the parts of the operation that are held together with tape and replace them with something that works. Each project starts with a problem and very little else: no spec, no existing tool, no one to hand the work to. The person in this seat figures out what should exist, builds the first version, puts it in front of the people who need it, and keeps improving it until it runs on its own. Then it's on to the next one.

The role reports to the Head of Robot Operations and Reliability.

Most of what it takes to run a much larger fleet hasn't been built yet. This role builds it. That means looking at how the operation runs today, finding where it breaks or slows down, and building what should be there instead. The work is tools, data, and the way the work itself gets done.

The work will keep changing as the fleet grows. What stays the same is the job itself: see the problem, build the fix, put it to use, and keep improving it until it runs on its own.

Some robot failures don't make sense at first. A sensor tests fine on the bench and fails on the floor. A robot runs clean for three weeks and then stops every afternoon at 2:00. This role leads those investigations. That means pulling logs, reading field reports and parts history, talking to the technician who was there, building a theory, testing it, and staying with it until the cause is found and the fix holds.

Someone who asks why a problem happened, not just how to make it stop, and who looks for the structure behind it: the process, the data, or the handoff that let it happen. Someone who, after watching a team struggle with the same problem twice, has already sketched a fix that keeps it from happening a third time, and built the first version. Someone who would rather own a result than report on one.

This can be an early-career role for someone with clear momentum, or a step up for someone five or more years in who is done reporting on problems they could have fixed. Either way, someone who learns fast, gets noticeably better every quarter, and wants the job to grow with the fleet.

The base salary range for this role is $100,000 to $140,000, depending on experience.

In office in Watertown, MA. Travel to customer sites and regional teams as needed, roughly 10–25%.

Along with a résumé, send a short note about something you built: what the problem was, what you made, and what happened after. Links, photos and code are all welcome.

As Tutor grows, so will our benefits. We’re continuing to invest in ways to support our team at work and beyond.