Robot Perception Engineer Jobs
Robot perception engineer jobs target teams building the sensor understanding layer that feeds autonomy and decision-making systems. Typical work includes multi-modal fusion, object detection and tracking, scene understanding, and performance validation across varied environments. You will often work with camera, lidar, and radar data while collaborating with SLAM and planning engineers to improve downstream behavior. Many organizations expect strong software engineering fundamentals alongside model and algorithm expertise, because perception systems must run reliably at production scale. These roles can involve both learned and geometric methods, depending on the stack and operating domain. If you specialize in computer vision for real-world robotics systems and want openings where perception quality directly affects field performance, this page provides a focused set of relevant jobs.
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Member of Technical Staff , Frontier AI & Robotics
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Staff AI Research Engineer - 3D Computer Vision
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Software Development Engineer II
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Senior Engineer, AV Behavior Evaluation
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Senior Technical Program Manager - Verification and Validation
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Thesis Work - Self-Adaptive Digital Twin for Robot Manipulation Through Continuous Real-Sim Discrepancy Learning
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Thesis Work on Safe and optimal planning and control for autonomous mining operations
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How to read a robot perception job description
Robot perception work sits between raw sensors and the decisions a robot makes. The strongest job descriptions make clear which sensors are used, what must run in real time, and whether the role is centered on learned models, geometric estimation, systems integration, or a mix of all three.
Sensors and calibration
Look for camera, depth, lidar, radar, IMU, or multi-sensor requirements plus calibration, synchronization, coordinate frames, and data-quality work. These are core production constraints rather than peripheral hardware tasks.
Scene understanding
Roles may cover detection, tracking, segmentation, 3D vision, pose estimation, state estimation, sensor fusion, or mapping. Some teams lean heavily on deep learning while others combine learned and geometric methods.
On-robot inference
For deployed systems, pay attention to C++ or Python ownership, latency budgets, GPU or edge inference, TensorRT-style optimization, reliability monitoring, and how perception outputs connect to planning, control, or teleoperation.
Search strategy
Relevant openings are not always titled Perception Engineer. Also search Computer Vision, Sensor Fusion, State Estimation, 3D Vision, Localization, and robotics ML roles when the description owns the robot's sensing pipeline.