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 Robotics Infrastructure Engineer: Systems, Infrastructure & Reliability We build robots that run 24/7 in production environments. We're looking for a hands-on engineer to own the reliability, infrastructure, and developer tooling that keeps our fleet running and our engineering team fast. You'll split your time between robot-side systems work, cloud infrastructure, and building automation that multiplies the team's output. A significant portion of this role involves working with AI coding agents. You'll direct autonomous agents to diagnose CI failures, triage production issues, run automated security and compliance checks, and execute multi-step engineering tasks. Knowing how to scope work for an agent, review its output critically, and build tooling that agents can use effectively is as important as writing the code yourself. What You'll Do Own robot-side software (Python): Maintain the on-robot codebase that orchestrates arms, cameras, sensors, and I/O. Debug production hardware/software failures and ship fixes fast Build and maintain infrastructure as code: Manage cloud infrastructure — identity and access management, CI/CD credentials, secrets, container registries, cluster autoscaling — using declarative configuration and reproducible builds Drive build system and packaging migrations: Own the transition of robot software packaging to reproducible, hermetic build systems. Maintain machine images, dev environments, and deployment pipelines Build simulation and testing infrastructure: Develop end-to-end simulation systems that validate robot behavior without physical hardware — camera projection, kinematics, placement validation, fleet-wide calibration Develop and operate AI-powered engineering automation: Build autonomous agents that run nightly CI triage, security audits, infrastructure compliance checks, and code quality sweeps. Design the interfaces and instructions that make agents effective at real engineering work Improve observability and health monitoring: Instrument robot software with metrics and structured telemetry. Build alerting that catches problems before humans notice them Work across the stack: Touch frontend, backend, protobuf definitions, deployment tooling, and cloud services as needed. No part of the system is someone else's problem What We're Looking For 3+ years of Python in a systems context — not web/ML Python, but the kind where you deal with processes, hardware I/O, async, and real-time constraints Strong Linux systems knowledge: Memory management, device management, systemd, containers, networking, kernel tuning Infrastructure as code experience: Declarative infrastructure and configuration management tools. You've managed IAM, CI runners, secrets, and machine images programmatically Experience with real hardware: Robot arms, depth cameras, grippers, force/torque sensors, pneumatics, or similar CI/CD ownership: You've not just used CI — you've owned it. Runner infrastructure, flaky test triage, build caching, GPU-enabled pipelines Comfort with AI coding agents: You've used tools like Claude Code, Cursor, Copilot Workspace, or similar to do real engineering work — not just autocomplete, but directing agents through multi-step debugging, refactoring, and infrastructure tasks. You understand their failure modes and know when to trust vs. verify Strong debugging instincts: You can go from a vague production symptom to root cause across hardware, OS, network, and application layers Bias toward shipping over perfecting: You fix, monitor, iterate. Your commit history has more fix: than feat: and you're proud of that Nice to Have NixOS or reproducible build system experience Experience building or operating autonomous engineering agents/bots Robotics simulation (kinematics, camera models, physics) gRPC / Protocol Buffers Managed network infrastructure, VPNs, overlay networks Time-series databases and observability stacks About the Work Style This is a high-autonomy, high-output role. On a typical day you might direct an AI agent to triage overnight CI failures while you debug a production robot issue, then spend the afternoon migrating a package to a new build system. You'll write a lot of code, but you'll also write a lot of prompts — and the best candidates will see those as the same skill. 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

Robotics Infrastructure Engineer: Systems, Infrastructure & Reliability
Own robot-side software (Python): Maintain the on-robot codebase that orchestrates arms, cameras, sensors, and I/O. Debug production hardware/software failures and ship fixes fast
Drive build system and packaging migrations: Own the transition of robot software packaging to reproducible, hermetic build systems. Maintain machine images, dev environments, and deployment pipelines
Build simulation and testing infrastructure: Develop end-to-end simulation systems that validate robot behavior without physical hardware — camera projection, kinematics, placement validation, fleet-wide calibration
Improve observability and health monitoring: Instrument robot software with metrics and structured telemetry. Build alerting that catches problems before humans notice them
Work across the stack: Touch frontend, backend, protobuf definitions, deployment tooling, and cloud services as needed. No part of the system is someone else's problem
3+ years of Python in a systems context — not web/ML Python, but the kind where you deal with processes, hardware I/O, async, and real-time constraints
Strong Linux systems knowledge: Memory management, device management, systemd, containers, networking, kernel tuning
Infrastructure as code experience: Declarative infrastructure and configuration management tools. You've managed IAM, CI runners, secrets, and machine images programmatically
Experience with real hardware: Robot arms, depth cameras, grippers, force/torque sensors, pneumatics, or similar
CI/CD ownership: You've not just used CI — you've owned it. Runner infrastructure, flaky test triage, build caching, GPU-enabled pipelines
Strong debugging instincts: You can go from a vague production symptom to root cause across hardware, OS, network, and application layers
Bias toward shipping over perfecting: You fix, monitor, iterate. Your commit history has more fix: than feat: and you're proud of that

Nice-to-haves

NixOS or reproducible build system experience
Experience building or operating autonomous engineering agents/bots
Robotics simulation (kinematics, camera models, physics)
gRPC / Protocol Buffers
Managed network infrastructure, VPNs, overlay networks
Time-series databases and observability stacks

Application prep

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

Keywords to mirror

gomachine learningaipythonci/cdml

Platform: lever
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance

401(K)

Pto

Paid Time Off