Applied Scientist II, Perception

Amazon is on a mission to redefine the future of automation. 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 machine learning, artificial intelligence, and advanced robotics to solve complex operational challenges at an unprecedented scale. Our fleet of robots spans hundreds of facilities globally, working in coordination to deliver customer excellence.

About the role

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 bridge the gap between theoretical research and real-world impact, bringing deep expertise in Computer Vision and Vision-Language Models (VLMs). This role offers the opportunity to work at the intersection of deep learning, large language models, and robotics, collaborating with world-class teams to pioneer breakthroughs in dexterous manipulation, locomotion, and human-robot interaction.

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
• Train ML models for deployment in simulation and real-world robots, identifying and documenting their limitations post-deployment
• Drive technical discussions within your team and with key stakeholders to develop innovative solutions
• Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives to help peers grow and succeed
• Mentor team members while maintaining significant hands-on contribution to technical solutions

Requirements

• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field
• 2+ years of experience building machine learning models for business applications
• Experience with Java, C++, or other programming languages
• Experience with neural deep learning methods and machine learning
• Publications at top-tier peer-reviewed conferences or journals

Preferred Qualifications

• Experience with large-scale distributed systems such as Hadoop, Spark
• 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

Pay

Base salary range: $171,600 - $222,200 USD annually (locations: San Francisco, Sunnyvale, CA). Your package will include sign-on payments, restricted stock units (RSUs), and comprehensive benefits such as health insurance, 401(k) matching, paid time off, and parental leave.

Benefits

• Health insurance (medical, dental, vision, prescription)
• Basic Life & AD&D insurance with option for supplemental life plans
• Employee Assistance Program (EAP) and Mental Health Support
• Medical Advice Line
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off and parental leave