Job description

About Tutor We believe robots will 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. The Role Own the software that makes robot data collection and experimentation dependable. Your initial focus will be our robot data-collection operation: connecting robots, operators, data storage, and research workflows so the team can run experiments repeatedly and trust the resulting data. You will define and deliver improvements across robot-side services, backend systems, telemetry, deployment, and operator tools. This is an autonomous individual-contributor role with significant system ownership, close collaboration with researchers and operators, and responsibility for maintaining what you ship. Responsibilities Own the technical approach and ongoing reliability of a major system supporting robot data collection and experimentation. Build and maintain robot-side and backend services, data pipelines, and tools that reduce operator effort and improve experiment throughput. Make system health, data completeness, sensor timing, and experiment progress observable; turn failures into actionable diagnostics. Improve deployment, configuration, testing, recovery, and rollback so changes and operations are repeatable. Diagnose incidents across device interfaces, Linux, networking, concurrency, and storage; deliver durable fixes and verify their effect. Prioritize work within team goals using evidence from researchers and operators, and communicate scope, risks, and tradeoffs. Improve engineering tools and runbooks, contribute useful technical reviews, and help colleagues operate and extend the system. Requirements Evidence of independently owning a substantial software system through design, deployment, operation, and difficult debugging. Strong Python software engineering, including maintainable code, automated tests, concurrency, and service interfaces. Practical Linux and networking knowledge, and experience deploying and operating services. Understanding of distributed-system failure modes, data integrity, and safe recovery from partial failures. Experience building observability and using it to diagnose incidents and improve reliability. Ability to work across unfamiliar system boundaries, define an approach to ambiguous problems, and collaborate with people who use the system daily. Nice to have Robotics, device fleets, teleoperation, edge computing, or synchronized sensor pipelines. C++ or Rust, containers, cloud infrastructure, infrastructure as code, or ML deployment. Operator tools and experiment platforms; effective use and critical review of AI-assisted engineering. What Success Looks Like Establish useful health and data-quality checks, operating documentation, and a prioritized plan for the agreed system. Resolve a recurring failure with a measured improvement in reliability or useful data collection. Make deployment and recovery repeatable and enable researchers and operators to diagnose routine issues Why Tutor? 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. Benefits We take care of our team so they can do their best work. At Tutor, you’ll get: Fully employer-covered health insurance, so you’re protected without the premium. A managed 401(k) to help you plan for the future. Generous time off: unlimited PTO and all federal holidays off for full-time salaried employees, and 16+ days of accrued paid time off plus 1.5x pay on federal holidays for hourly employees. Regular in-office meals and team social events throughout the year. As Tutor grows, so will our benefits. We’re continuing to invest in ways to support our team at work and beyond. Tutor Intelligence is an equal opportunity employer and welcomes applicants from all backgrounds.

Requirements

Must-haves

Own the technical approach and ongoing reliability of a major system supporting robot data collection and experimentation.
Build and maintain robot-side and backend services, data pipelines, and tools that reduce operator effort and improve experiment throughput.
Make system health, data completeness, sensor timing, and experiment progress observable; turn failures into actionable diagnostics.
Improve deployment, configuration, testing, recovery, and rollback so changes and operations are repeatable.
Diagnose incidents across device interfaces, Linux, networking, concurrency, and storage; deliver durable fixes and verify their effect.
Prioritize work within team goals using evidence from researchers and operators, and communicate scope, risks, and tradeoffs.
Improve engineering tools and runbooks, contribute useful technical reviews, and help colleagues operate and extend the system.
Evidence of independently owning a substantial software system through design, deployment, operation, and difficult debugging.
Strong Python software engineering, including maintainable code, automated tests, concurrency, and service interfaces.
Practical Linux and networking knowledge, and experience deploying and operating services.
Understanding of distributed-system failure modes, data integrity, and safe recovery from partial failures.
Experience building observability and using it to diagnose incidents and improve reliability.
Ability to work across unfamiliar system boundaries, define an approach to ambiguous problems, and collaborate with people who use the system daily.

Nice-to-haves

Robotics, device fleets, teleoperation, edge computing, or synchronized sensor pipelines.
C++ or Rust, containers, cloud infrastructure, infrastructure as code, or ML deployment.
Operator tools and experiment platforms; effective use and critical review of AI-assisted engineering.
What Success Looks Like
Establish useful health and data-quality checks, operating documentation, and a prioritized plan for the agreed system.
Resolve a recurring failure with a measured improvement in reliability or useful data collection.
Make deployment and recovery repeatable and enable researchers and operators to diagnose routine issues

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

gomachine learningpythonrustmlai

Platform: lever
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance

401(K)

Pto

Paid Time Off