Sr. Applied Scientist, AWS Just-Walk-Out Science Team

About the role

As part of the AWS Solutions organization, we aim to provide business applications that accelerate our customers' businesses through intuitive and differentiated technology solutions. We blend vision with curiosity and leverage Amazon’s real-world experience to build turnkey solutions that are no-brainers to buy and easy to use.

Key job responsibilities

• Tackle problems spanning various domains such as computer vision, image recognition, machine learning, real-time and distributed systems.
• Develop and implement advanced visual reasoning systems that understand complex spatial relationships and object interactions in real-time.
• Design autonomous AI agents capable of making intelligent decisions based on visual inputs, understanding customer behavior patterns, and adapting to dynamic retail environments.
• Work on systems that perform complex scene understanding, reason about object permanence, and predict customer intentions through visual cues.

About the team

Just Walk Out (JWO) is a checkout-free store where customers can grab and go without lines. The technology behind this experience uses a combination of computer vision, sensor fusion, and advanced machine learning. Our goal is to be Earth's most customer-centric company and we're just getting started.

Basic Qualifications

• PhD or PhD-equivalent research experience and 3+ years of building models for business applications
• PhD or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience with programming languages like Python, JavaScript, Go, .Net, Java or equivalent
• Experience with machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications
• Experience in patents or publications at top-tier peer-reviewed conferences or journals

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
• Experience with advanced computer vision techniques including scene graph generation, visual relationship detection, and spatial reasoning
• Knowledge of modern visual-language models and multi-modal AI systems
• Experience implementing reinforcement learning for autonomous agent behavior
• Experience in professional software development