Staff Robotics Engineer - Perception at Gather AI

<p><strong>About Us</strong></p> <p>Are you ready to build the future of the supply chain? At Gather AI, we’re not just creating software; we’re pioneering a new era of warehouse intelligence. We’ve developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining “on-time, in full” delivery.</p> <p>If you’re looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We’re leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.</p> <p><strong>About the Team</strong></p> <p>This role sits at the intersection of our Autonomy, Machine Learning, Hardware, and Product teams. You will collaborate with engineers across drone, MHE Vision, and embedded systems, partner with Product on scanning accuracy requirements, and work with Hardware and Operations on camera mounting, lighting, and real-world warehouse deployment.</p> <p><strong>About the Role</strong></p> <p>We are seeking a <strong>Staff Robotics Engineer - Perception</strong>&nbsp;to take full technical ownership of one of Gather AI's two production platforms — our drone-based inventory scanning system or our MHE Vision product — deployed today in customer warehouses. You'll bring systems-level rigor to a platform that already works, with a mandate to make it faster to deploy, easier to operate, and more reliable at scale.&nbsp;</p> <p>This is a high-ownership, high-impact role, critical to the quality of every scan our system performs. You will drive technical direction and deliver measurable impact on production systems serving real customers.</p> <p><strong>What You’ll Do</strong></p> <ul> <li>Own the camera and imaging subsystem audit across MHEV and Modal: characterize existing performance (barcode decode rates, read distances, motion blur impact) and identify top bottlenecks</li> <li>Evaluate and select camera and sensor hardware — specifying resolution, sensor size, lens selection, and exposure control for industrial warehouse environments</li> <li>Implement and tune auto-exposure, gain control, and lighting strategies for variable warehouse lighting conditions, including motion blur mitigation for moving platforms</li> <li>Develop image quality metrics and production monitoring to maintain system performance as deployments scale</li> <li>Collaborate with the ML team to ensure perception model inputs meet training and inference quality requirements; contribute to next-generation capabilities such as damage detection and label reading</li> <li>Work with the hardware team on camera mounting, vibration/damping, and lens placement to optimize system-level performance</li> </ul> <p><strong>What You’ll Need</strong></p> <ul> <li>5+ years of experience in machine vision, imaging systems, or perception engineering</li> <li>Deep expertise in camera systems: sensor selection, lens specification, resolution analysis, pixels-on-target calculations, and exposure control for industrial applications</li> <li>Hands-on experience with motion blur analysis and mitigation — rolling vs global shutter trade-offs, exposure budgeting relative to platform velocity</li> <li>Strong Python and C++ proficiency with OpenCV and camera SDK experience (FLIR, Lucid, Basler, or similar); familiarity with GigE Vision or USB3 Vision standards</li> <li>BS or MS in Electrical Engineering, Optics, Physics, Computer Science, or a related field</li> </ul> <p><strong>Nice to Have</strong></p> <ul> <li>Experience with drone or robotics perception systems (gimbal stabilization, triggering, onboard compute constraints)</li> <li>Optical design or lens selection experience (MTF analysis, depth of field, distortion characterization)</li> <li>Edge compute and embedded vision experience (NVIDIA Jetson, FPGA-based image processing)</li> <li>Familiarity with classical and deep learning perception algorithms and how image quality affects model performance</li> </ul>