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This is the sensor and perception authority at the top of our robotics solutioning funnel. When a client requirement comes in — egocentric data collection, teleoperation, field deployment — you are the person who determines what a given sensing setup can actually produce, whether it meets the requirement (sub-centimeter positional accuracy, hand-keypoint fidelity, a usable 3D mesh), and, when it doesn't, what device or configuration will.
You are deliberately device-agnostic: XR headsets (e.g., Pico), optical/mocap suits (e.g., OptiTrack), data gloves, depth cameras, and IMU-based rigs are all fair game — you reason about the feed, the geometry, and the physics behind it rather than any single product. You work shoulder-to-shoulder with Product, Engineering, and Solutions to certify device feeds for pilots before we commit to a client, and you keep scanning the market so we adopt new sensing hardware ahead of demand, not behind it.
This is the sensor and perception authority at the top of our robotics solutioning funnel. When a client requirement comes in — egocentric data collection, teleoperation, field deployment — you are the person who determines what a given sensing setup can actually produce, whether it meets the requirement (sub-centimeter positional accuracy, hand-keypoint fidelity, a usable 3D mesh), and, when it doesn't, what device or configuration will.
You are deliberately device-agnostic: XR headsets (e.g., Pico), optical/mocap suits (e.g., OptiTrack), data gloves, depth cameras, and IMU-based rigs are all fair game — you reason about the feed, the geometry, and the physics behind it rather than any single product. You work shoulder-to-shoulder with Product, Engineering, and Solutions to certify device feeds for pilots before we commit to a client, and you keep scanning the market so we adopt new sensing hardware ahead of demand, not behind it.
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ROS / ROS2 exposure.
Connections into the research / sensing-hardware ecosystem (e.g., IISc, sensor labs).
A track record of device profiles, feed specs, or evaluation write-ups that other engineers reused.
Awareness of the robot-learning and VLA pipelines that consume this sensor data downstream.
Languages: Python (NumPy, OpenCV, Open3D)
Perception / 3D: camera models, projection, calibration, point-cloud processing
Sensing: XR headsets, optical/IR mocap, depth cameras, IMU, data gloves
Tooling: calibration toolkits; ROS / ROS2 exposure a plus
Core Areas: sensor feasibility, calibration, tracking/keypoints, 3D geometry, accuracy verification
Every robotics pilot enters delivery with a sensing approach validated against the client's actual accuracy / quality requirement.
Device-selection decisions are made on evidence, not assumption — fewer “the tracking is off” surprises after commitment.
New sensing hardware is evaluated and ready before client demand forces it.
Product and Engineering treat this role as the trusted first answer to “can this device give us the data we need?”
Flex hours: Given global client coverage, this role includes flexibility for periodic night-shift / time-zone-overlap hours to support US/EU engagements as required.
Canadian private BPO and digital-services company delivering customer experience, AI, data, IT, and trust-and-safety services for brands.
Visit company websiteJobs and hiring trendsFull-time
Mid · 3+ years experience
Onsite
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