Senior Applied Scientist, Last Mile Delivery

Amazon
Santa Clara, California, USA2025-11-26ONSITE

About the job

Join Amazon's Last Mile Technology Revolution! Are you ready to reshape the future of logistics? Join us in transforming how millions of packages reach their final destination through state-of-the-art technology and innovation! The Last Mile Technology organization is pioneering advanced solutions that are revolutionizing Amazon Logistics (AMZL). Our mission is to create intelligent, efficient, and scalable systems that will transform the delivery experience. We're building the future of last-mile logistics while maintaining Amazon's highest standards for safety and reliability. The Last Mile challenge is a fascinating blend of real-world complexity and technological innovation. We're tackling multidimensional problems that involve enabling AI agents to perceive and navigate complex delivery environments, understanding dynamic scenes through visual data, and adapting to everything from unexpected obstacles to varying weather and lighting conditions – all while ensuring every package arrives safely as per our promise.

Responsibilities

design and implement deep learning models for visual perception, build algorithms that enable decision-making, and create robust systems that allow AI agents to operate safely across diverse geographical areas. Your research must excel in environments ranging from dense urban centers to suburban neighborhoods, each presenting unique visual and navigational challenges that require innovative solutions in perception and control

Qualifications

Minimum

PhD in Computer Science, Electrical Engineering, Robotics, or a related field; 3+ years of experience applying computer vision, machine learning, or deep learning techniques to real-world problems; Experience building and deploying production-level computer vision systems; Strong programming skills in Python and/or C++; Experience with deep learning frameworks such as PyTorch or TensorFlow

Preferred

Experience with autonomous systems, robotics, or self-driving technology; Experience with sensor fusion (cameras, LiDAR, radar); Publications in top-tier computer vision or robotics conferences (e.g., CVPR, ICCV, ECCV, CoRL, RSS); Experience with reinforcement learning or control theory; Familiarity with edge computing and embedded systems for real-time inference