Applied Scientist II, Perception

Amazon
USA, CA, SAN FRANCISCO2026-06-24ONSITE

About the job

Amazon is on a mission to redefine the future of automation and is looking for exceptional talent to help lead the way. As an Applied Scientist in Robot Perception, you will develop and deploy state-of-the-art perception algorithms that enable robots to understand and interact with the physical world. You will bring deep expertise in Computer Vision and a nuanced understanding of modern Vision-Language Models (VLMs) to innovate and push the boundaries of what's possible.

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

PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field

2+ years of building machine learning models for business application experience

Experience with Java, C++, or other programming languages

Experience with neural deep learning methods and machine learning

Have publications at top-tier peer-reviewed conferences or journals

Preferred

Experience with large scale distributed systems such as Hadoop, Spark etc.

PhD in Robotics, with a focus on Robot Perception

Experience leading research initiatives in full-stack robotics or foundation models

Track record of successful production robotics deployments

History of technical leadership and team mentorship

Experience bridging research with practical engineering implementation in robotics systems

Extensive programming skills in Python and PyTorch/JAX