Fleet Reliability Engineer

3 to 5 years in robotics, mechatronics, hardware test, or reliability engineering, with significant time on fielded hardware rather than lab prototypes.

Genuinely hands-on instincts. You are comfortable at the bench with a soldering iron, multimeter, and calipers, and you can tear down, repair, and re-commission electromechanical assemblies without waiting on another team.

An understanding of how actuators fail mechanically, including backlash, wear, preload loss, and end-stop damage, and the ability to connect physical evidence to design causes. You will not be doing large structural design or FEA, but you should hold your own in a design review.

Working knowledge of robot control: impedance and torque-controlled actuators, force-control parameters, and controller state lifecycles (boot, e-stop, reconnect). Enough to tune deployed behavior and recognize when a "hardware" fault is actually a controls bug. You do not need to design controllers from scratch.

Strong Python for data analysis and tooling, plus solid time-series and signal-statistics instincts around noise floors, drift, persistence rules, and spotting when an alert is just a tiny denominator.

Fluency with actuators and motor control: quasi-direct-drive systems, encoders, torque and current telemetry, CAN, and calibration and zeroing procedures.

Experience with observability stacks (Datadog or similar) and git and PR-based workflows.

Rigor about evidence. You distinguish measured from commanded and correlation from cause, and you will not ship a conclusion or set a baseline on contaminated data.

A bias toward small, verifiable scope. You deliver the stated goal, flag adjacent issues once, and do not gold-plate.

Experience with teleoperation systems, VR interfaces, or data-collection fleets.

Prior work on hardware qualification (EVT, DVT, PVT) or manufacturing and incoming test.

Simulation sanity-checking in MuJoCo.

A track record of building tools and SOPs that other engineers actually adopt.

At Dyna Robotics, we build technology for the real world, which requires a team as diverse as the environments our robots inhabit. We are an equal opportunity employer committed to technical rigor and mutual respect.

Don't let a checklist stop you. Data shows that underrepresented groups often only apply if they meet 100% of the criteria. We value problem-solving and grit over keyword matching. If you're passionate about closing the loop between deployed robots and better models, we want to hear from you, even if you don't check every box.