Lead Robotics Engineer

You own the physical end of our robot data business: the robots, the rigs, the sensors, the operators, and the guarantee that every hour we capture is an hour a customer will accept and a model can…

Lead Engineer — Teleoperation & Data Capture Systems
Team: Robotics Division Location: Abu Dhabi, UAE — with regular on-site presence at our Dubai collection facility Reports to: Director of AI & Engineering Type: Full-time, on-site

The role in one line

You own the physical end of our robot data business: the robots, the rigs, the sensors, the operators, and the guarantee that every hour we capture is an hour a customer will accept and a model can actually learn from.

We operate one of the region's largest teleoperation and egocentric data collection programmes, supplying training data to frontier humanoid robotics companies and national research institutes. We run humanoid fleets under teleoperation, wearable egocentric capture rigs, and a growing network of vendor and in-house collection sites. Our data platform — ingestion, quality gates, provenance verification, LeRobot normalisation, self-service delivery — is already in production and led by a dedicated MLOps lead.

What we need now is that person's counterpart on the physical side. Today our throughput is capped by robot uptime, rig reliability, and the time it takes to qualify a new capture configuration. We are standing up a second collection facility to roughly double monthly delivered hours. You will be the technical owner of that. This is a hands‑on senior role with team leadership attached.

You will spend real time on the floor with robots, cameras and cabling, not only in design reviews.

Capture hardware and rig engineering
- Select, qualify and integrate the full capture stack: egocentric cameras, wearable rigs and smart glasses, depth and stereo modules, VR headsets for teleoperation and head‑pose telemetry, hand‑tracking and biosignal sensors, on‑robot sensor suites.

- Run hardware evaluations against explicit acceptance criteria — field of view, resolution, frame timing stability, exposure behaviour under our lighting conditions, ergonomics over a full operator shift, failure modes.

- Work with external hardware partners and contract manufacturers on custom capture devices: requirements, design review, pilot builds, qualification, and the decision of when a vendor rig is good enough to scale.

- Own calibration: camera intrinsics and extrinsics, multi‑camera and hand–eye calibration, IMU alignment, and the procedures that let a technician re‑calibrate a rig correctly without you in the room.

Time synchronisation and data integrity
- Guarantee temporal alignment across heterogeneous sensors running at different rates — video, high‑rate biosignals, joint states, head and hand pose, control commands.

- Design the clock discipline: hardware triggering, PTP/NTP strategy, common time base,drift characterisation, and the measurement method that proves alignment rather than assuming it.

- Diagnose and eliminate sub‑frame and tens‑of‑milliseconds offsets. This is not a theoretical requirement — misalignment here is the single fastest way to make a dataset worthless.

Fleet operations and throughput
- Own uptime and delivered hours for the humanoid teleoperation fleet. Maintenance schedules, spares strategy, wear‑part replacement cycles, failure logging, MTBF tracking, and repair turnaround.

- Set and hit a monthly delivered‑hours target. Diagnose the bottleneck when we miss — robot availability, operator capacity, rig failures, or rework from QA rejections.

- Build the operator function: recruiting, training curriculum, shift structure, per‑operator quality tracking, and the feedback loop that turns a rejection reason into…