Applied Scientist Ii, Aws Just-walk-out Science Team

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

The Applied Scientist II role on the AWS Just-Walk-Out Science Team focuses on developing and implementing advanced visual reasoning systems and autonomous AI agents for a checkout-free retail environment. This involves understanding complex spatial relationships, object interactions, customer behavior, and adapting to dynamic retail settings using computer vision, sensor fusion, and machine learning.

What you'd actually do

  1. As an Applied Scientist, you will help solve a variety of technical challenges and mentor other scientists.
  2. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations.
  3. A key focus of this role will be developing and implementing advanced visual reasoning systems that can understand complex spatial relationships and object interactions in real-time.
  4. You'll work on designing autonomous AI agents that can make intelligent decisions based on visual inputs, understand customer behavior patterns, and adapt to dynamic retail environments.
  5. This includes developing systems that can perform complex scene understanding, reason about object permanence, and predict customer intentions through visual cues.

Skills

Required

  • 3+ years of building models for business application 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++
  • 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

Nice to have

  • 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

What the JD emphasized

  • building models for business application experience
  • Research publications in computer vision, deep learning or machine learning at peer-reviewed workshops, conferences or journals
  • 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
  • AI agent architecture design
  • visual-language models
  • multi-modal AI systems
  • reinforcement learning for autonomous agent behavior

Other signals

  • developing and implementing advanced visual reasoning systems
  • designing autonomous AI agents
  • understand customer behavior patterns
  • adapt to dynamic retail environments
  • perform complex scene understanding
  • reason about object permanence
  • predict customer intentions through visual cues