Applied Scientist II, Perception

Description

Amazon 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.

At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started.

As a 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. Bringing deep expertise in Computer Vision and a nuanced understanding of the capabilities and limitations of modern Vision‑Language Models (VLMs), you will innovate boldly and push the boundaries of what's possible.

Our vision for the Perception layer is ambitious: to enable seamless, intelligent interaction between the user, the robot, and its environment. This is a rare opportunity to work at the intersection of deep learning, large language models, and robotics — contributing to research that doesn't just advance the field, but reshapes it. You will collaborate with world‑class teams pioneering breakthroughs in dexterous manipulation, locomotion, and human‑robot interaction, all at an unprecedented scale.

• 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

• Train ML models for deployment in simulation and real‑world robots, identify and document their limitations post‑deployment
• Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations
• Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team
• Mentor team members while maintaining significant hands‑on contribution to technical solutions

• 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

• 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

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