Senior Applied Scientist

Amazon • San Francisco, CA

1d • $192,200 - $260,000 • Onsite

About The Position

Amazon Industrial Robotics is redefining the future of automation by building advanced robotic systems that integrate AI, control systems, and mechanical design for adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic environments. We leverage machine learning, artificial intelligence, and advanced robotics to solve complex operational challenges at a global scale. As a Sr. Applied Scientist in Robot Perception, you will develop and deploy state-of-the-art perception algorithms enabling robots to understand and interact with the physical world, bridging the gap between research and real-world impact. Your expertise in Computer Vision and Vision-Language Models (VLMs) will drive innovation in the Perception layer for seamless, intelligent interaction between users, robots, and their environments. This role offers a unique opportunity to work at the intersection of deep learning, large language models, and robotics, contributing to research that reshapes the field. You will collaborate with world-class teams pioneering breakthroughs in dexterous manipulation, locomotion, and human-robot interaction at an unprecedented scale.

Requirements

• 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

Nice To Haves

• 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

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, 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

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree