Robotics Software Engineer, Perception

Job description

Job responsibilities

• Define and drive the multi-year technical roadmap for the Perception Team; align perception capabilities with the broader Autonomous Factory Systems strategy and surface upstream dependencies and risks early
• Lead architecture of the full perception pipeline — object detection and tracking, semantic and instance segmentation, 6-DoF pose estimation, and scene understanding — designed for the reliability and throughput…
• Define the integration surface between perception and adjacent systems (motion planning, manipulation, control, simulation);
• Drive sensor fusion strategy across LiDAR, structured light, RGB, and depth cameras; collaborate with hardware teams on sensor selection and calibration pipelines
• Establish rigorous practices for the team: data collection and labeling pipelines, model training and evaluation workflows, deployment practices, and validation criteria across simulation and real-world environments
• Raise the technical bar in hiring — define role requirements, conduct technical interviews, and assess candidates with the domain depth the field demands;
• Represent perception in cross-functional design reviews and planning; engage with hardware vendors and research collaborators where relevant
• Continuously evaluate state-of-the-art research; make deliberate, justified decisions about when and how to incorporate advances into production systems

Job requirements

• 10+ years of software engineering in computer vision, robotics perception, or autonomous systems, with a track record of technical leadership at Staff or Principal level (or equivalent scope)
• Expert-level command of 3D computer vision: point cloud processing, depth estimation, stereo and structured light systems, multi-view geometry, and/or LiDAR-based algorithms in production
• Strong machine learning foundations — model architecture, training infrastructure, and production deployment — with the judgment to know when and how to apply learned approaches versus classical methods
• Experience in manufacturing, logistics, or other applied robotics environments — familiarity with the reliability and safety constraints that production deployment demands beyond the lab
• Experience building and deploying real-time perception systems under hard latency and reliability constraints
• Strong proficiency in C++ and Python; demonstrated ability to write production-quality code and hold a high bar in technical review
• Proven ability to define architecture across a domain, make and communicate high-stakes technical decisions, and build alignment across teams and organizational boundaries
• Experience contributing meaningfully to technical hiring — defining role requirements, evaluating candidates, and helping raise team caliber over time