Senior Applied Scientist, Gem

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

Senior Applied Scientist role focused on shaping visual shopping experiences using agentic AI, multimodal personalization, and real-time image/video generation. The role involves defining scientific vision, architecting multimodal understanding and generation systems, and establishing evaluation frameworks for visual agentic experiences. It requires strong research skills, practical engineering instincts, and influencing cross-functional teams, with a focus on delivering scalable solutions and contributing to publications/patents.

What you'd actually do

  1. Define the research roadmap and advance core science primitives for vision and language understanding, visual content generation and editing, virtual try-on, and automated quality assurance via state-of-the-art computer vision, machine learning, and generative AI
  2. Architect visual agentic systems, making high-judgment trade-offs across visual quality, relevance, latency, cost, and long-term extensibility
  3. Establish evaluation frameworks, metrics, and success criteria for the team's scientific initiatives, institutionalizing rigorous validation across customer touch points
  4. Own end-to-end delivery of complex, ambiguous research initiatives from problem formulation through experimentation to production deployment, with minimal guidance
  5. Identify whitespace opportunities by staying at the forefront of AI/ML advances and translating them into actionable research directions with clear customer and business impact

Skills

Required

  • Computer Vision
  • Generative AI
  • Machine Learning
  • Python
  • Java
  • C++

Nice to have

  • neural deep learning methods
  • generative AI tools to enhance workflow efficiency

What the JD emphasized

  • own and define the scientific vision, strategy, and roadmap
  • architecting and advancing core science primitives
  • establish the technical direction
  • define and institutionalizing robust evaluation frameworks and metrics
  • proven track record of connecting scientific work to customer and business outcomes at scale
  • rigorous research skills and practical engineering instincts
  • demonstrated ability to navigate ambiguity, make high-judgment trade-offs, and drive alignment across competing priorities
  • contribute to the broader scientific community through publications, patents, and internal knowledge sharing
  • shape the technical strategy for visual commerce through applied AI research
  • building the systems that will define how hundreds of millions of customers discover and evaluate products and styles through visual experiences

Other signals

  • visual shopping experiences
  • agentic AI capabilities
  • multimodal understanding
  • visual content generation
  • personalized virtual try-on
  • automated quality assurance
  • real-time image/video generation