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Robotics Reliability Engineer - Motors, Mechanisms and Electronics

Maticrobots
CompanyMaticrobots
CategoryEngineering
LocationMenlo Park
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted7 May 2025
Last verified11 Aug 2026
SourceEmployer ATS (ashby)
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Description
COMPANY OVERVIEW Each year, 2.5 trillion hours are spent on household chores. At Matic, we’re on a mission to recapture that lost time, and we’re doing it by revolutionizing home robotics. Our first product, also called Matic, is a Wall-E-esque floor cleaning robot. We've built what amounts to "full self-driving in the home” with real-time 3D mapping, adaptive path-tracking, and a precise semantic understanding of the home. Our breakthroughs in spatial AI allow Matic to work reliably in real homes, using only RGB cameras and neural networks running on-device. PRIVACY FIRST What happens in the home, stays in the home. Our robots are private by design, with all data processing performed by the robot itself, not in the cloud. OUR APPROACH Before the iPhone, consumers adopted several distinct devices; cell phones, PDAs, and portable music players each served a particular need. We believe in a similar progression for home robotics, starting with single-purpose robots and building iteratively toward more complex capabilities over time. OUR CULTURE Matic is a tight-knit and collaborative team, singularly focused on building products our customers will cherish. We're ultra-hardworking people committed to solving tough problems that save precious time and energy. ABOUT THE ROLE As a Robotics Reliability Engineer, you own reliability across our subsystems, especially motors, mechanisms, and electronics, from the drawing board all the way into customers’ homes. The role has two halves, and you live in both. Before launch, you are our design-for-reliability conscience. You partner with design engineers to predict how a part or subsystem could fail, run DFMEA to map those failure modes, and define how we prove them out: which tests, accelerated how, for how long, and with how many samples. You set the reliability targets and the plan to hit them, so problems get caught on the bench instead of in someone’s living room. After launch, once robots are in real homes, the real data starts coming from every direction: support tickets, customers posting when something breaks, robots sent back for repair, and the motor and sensor telemetry customers consent to share. A robot returned for one problem is often broken in five other ways the customer never noticed, so you tear it down and find all of them. Your job is to see every way a robot is failing or could fail, keep track of all of it, and turn that signal into action: new tests and test setups where we need them, and clear input on which failure modes are under-prioritized and need engineering bandwidth. WHAT YOU’LL DO - Partner with design engineers to understand the physics of failure and design accelerated test methods that represent real field behavior - Run DFMEA and set reliability targets early, predicting failure modes before launch and specifying the tests, sample sizes, durations, and acceleration factors needed to prove the design out - Collaborate with our reliability design engineers to design and build test setups for different loading scenarios such as fatigue, vibration and shock, and temperature and humidity - Monitor every way our robots fail in the field, across support tickets, social media, returns, and telemetry, and tear down returned units to find failures the customer never reported - Own and track the full catalog of field and potential failure modes across the fleet, and drive each one to resolution through either testing or a design change - Build and own the analytics on motor and sensor telemetry that surface where features and parts are failing at scale - Perform root cause failure analysis at every stage, from early bench testing through field returns - Prepare concise and detailed test plans, drive test execution, analyze test reports, and present results to all relevant stakeholders - Influence design direction and prioritization by flagging which failure modes are under-prioritized and where desig