Operations Engineer

Who you are

• 0–5 years of experience in a production environment supporting and improving complex robotics or hardware/software systems, or a minimum of 2 years of experience combined with a Bachelor of Science degree in Computer Science, Software Engineering, or Robotics
• Strong technical curiosity and debugging skills, including the ability to read technical logs and interpret data across the hardware/software boundary
• Scripting and data fluency — comfortable with Python, SQL, or equivalent, with AI tools as force multipliers, to analyze production data and build and ship lightweight internal tools yourself
• Demonstrated excellence in communication and documentation — this role's output is often a runbook, an interface, or a well-specified request, and all three have to be clear
• Ability to work autonomously with minimal supervision, across multiple sites and stakeholder groups
• Sound judgment under pressure: you can stabilize an issue in the moment without losing the long-term thread, and you know when a fix is yours to ship versus when it belongs to a dev team
• Comfortable hands-on with hardware: rigs, sensors, cameras, cabling, and the physical realities of a production floor
• In-person role at our data collection sites, with regular presence on the floor and travel between sites as needed
• Flexibility to support evening shifts and occasional urgent coverage — collection runs on a shift schedule, and blockers don't wait for business hours
• Work location includes production-floor environments with variable temperatures

What the job involves

• Nimble Brain turns real-world operational data into the training sets, evaluations, and feedback loops that make our robots smarter every day
• That data comes from our collection sites — operators, supervisors, rigs, and capture systems running shift after shift — and every hour a rig is down, a calibration drifts, or a workflow jams is an hour of robot learning lost
• As an Operations Engineer on Nimble Brain, you are the glue between operations and engineering
• You'll be the technical backbone of our collection sites: diagnosing and resolving the issues that site technicians can't, translating floor pain into engineering priorities and engineering changes into floor-ready workflows, and constantly removing blockers before they cost a shift — then building the tools that prevent them from coming back
• This role is equal parts triage and engineering — and most importantly, knowing which one a given issue calls for
• Sometimes the right answer is the workaround that keeps a shift collecting; sometimes it's pulling a recurring problem out of the rotation and killing it for good with a tool, an interface, or a procedure anyone on the floor can run. Most times, it's both
• And every fix carries a second judgment: is this one you build and ship yourself, AI tools in hand — or a true dev-team fix, and if so, whose?
• Quick action in the moment, long-term consequences in mind: stabilize now, industrialize what earns it, route what's bigger, and build the observability that makes tomorrow's issues smaller than today's
• Act as first-line technical support beyond routine maintenance for our data collection sites: diagnose and resolve issues across rigs, teleoperation and capture systems, and the software that runs them
• Industrialize engineering workflows into floor-ready tools: build the operator-facing interfaces, checklists, and automations that let work once requiring an engineer run reliably in production — setup, calibration, diagnostics, and everything like them
• Build observability for the collection operation: rig health, calibration drift, capture pipeline status, and the alerts that surface problems before they cost accepted episodes
• Be the bridge between ops and engineering: own the routing call on every issue — fix it yourself, or spec it as a prioritized, well-defined request to the right engineering team — and translate engineering changes back into documentation, SOPs, and training the sites can absorb without losing a shift
• Partner with site technicians on the hardware line: they own routine maintenance and physical upkeep; you own systems-level diagnosis, tooling, and the escalation path into engineering
• Use a data-driven approach to prioritize: quantify which failures and workflow frictions cost the most accepted episodes, fix in that order, and revisit the workarounds you've shipped to decide which have earned a permanent fix
• Support site ramps and new-site bring-up: rig installation, station configuration, and getting new floors to steady state fast
• Create and maintain documentation and runbooks in collaboration with technicians, supervisors, and engineering — so sites self-serve more every month and escalate less