Applied Scientist II, AWS Just-Walk-Out Science Team

About the role

As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges.

Key job responsibilities

• Entrepreneurial mindset, wearing many hats, working in a highly collaborative environment that’s more startup than big company
• Tackle problems spanning various domains: computer vision, image recognition, machine learning, real-time and distributed systems
• Help solve a variety of technical challenges and mentor other scientists
• Tackle challenging, novel situations every day and work with multiple technical teams at Amazon in different locations
• Develop and implement advanced visual reasoning systems that can understand complex spatial relationships and object interactions in real-time
• Design autonomous AI agents that can make intelligent decisions based on visual inputs, understand customer behavior patterns, and adapt to dynamic retail environments

About The Team

Just Walk Out (JWO) is a new kind of store with no lines and no checkout—you just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go! Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your account and send you a receipt.

Basic Qualifications

• 3+ years of building models for business applications experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience with deep learning libraries such as PyTorch, TensorFlow, MxNet
• Research publications in computer vision, deep learning or machine learning at peer-reviewed workshops, conferences or journals
• Experience with programming languages such as Python, Java, C++
• Demonstrated experience in any of the following: visual reasoning, generative AI, transformers, multi-modal models, video analysis, action/activity understanding, object detection and tracking, 3D geometry, numerical optimization, Simultaneous Localization and Mapping (SLAM), time series analysis

Preferred Qualifications

• Experience in designing and implementing visual reasoning systems that can understand and interpret complex spatial relationships
• Demonstrated experience in AI agent architecture design, including decision-making frameworks and behavioral modeling
• Knowledge of advanced computer vision techniques including scene graph generation, visual relationship detection, and spatial reasoning
• Experience implementing reinforcement learning for autonomous agent behavior
• Experience in professional software development