About the job
Amazon Industrial Robotics is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. As a Sr. Applied Scientist in Robot Perception, you will be at the forefront of this transformation. You will develop and deploy state-of-the-art perception algorithms that enable robots to truly understand and interact with the physical world — bridging the gap between theoretical research and real-world impact.
Responsibilities
Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding
• Lead research initiatives in computer vision, sensor fusion and 3D perception
• Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities
• Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment
• Mentor junior scientists and engineers; contribute to a culture of technical excellence
• Define and track key metrics to measure perception system performance in real-world environments
• Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents
Qualifications
Minimum
Experience programming in Java, C++, Python or related language
PhD in Computer Science, Electrical Engineering, Robotics, or a related field
4+ years of hands-on experience in computer vision, 3D perception, or sensor fusion
Strong proficiency in Python and/or C++
Experience with deep learning frameworks (PyTorch, TensorFlow, or equivalent)
Proven track record of delivering ML/perception systems to production
Strong publication record or equivalent applied research experience
Preferred
Experience with robotic perception in real-world, unstructured environments
Familiarity with ROS/ROS2 and robotics middleware
Experience with point cloud processing (PCL, Open3D) and multi-modal sensor fusion
Knowledge of SLAM, localization, or mapping systems
Experience with large-scale data pipelines and distributed training
Prior experience in warehouse automation, autonomous vehicles, or industrial robotics