Robotics Research Infrastructure

Tutor IntelligenceWatertown, MassachusettsOn-siteFull-timeStaff, 8–12 yearsListed 4 hours ago

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About this role

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

At Tutor, engineers and researchers in R&D hold the title Member of Technical Staff (MoTS). Our job postings use familiar titles to help candidates find us; your level is determined through the interview process. Work evolves with the team’s needs, and we value the technical depth and collaborative judgment that let people contribute across changing projects.