Applied Scientist Ii, Scot Oss - Sourcing Execution & Performance

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

This role focuses on building agentic GenAI workflows for supply chain optimization, specifically for vendor coaching, evaluation, and collaborative inventory planning. It involves developing and deploying algorithms, collaborating with engineering teams on training and inference pipelines, and driving technical standards.

What you'd actually do

  1. Build solutions to enable collaborative inventory planning with vendors through agent to agent collaboration or humans-in-the loop collaborative methods
  2. Leverage and develop agentic GenAI workflows to automate the end-to-end vendor coaching and evaluation
  3. Drive the full development cycle from whiteboarding new algorithmic approaches to production-scale deployments
  4. Collaborate with SDEs to build high-performance, distributed training and inference pipelines; translate complex scientific concepts into scalable, production-grade code
  5. Mentor and provide technical guidance to other team members on complex projects

Skills

Required

  • building models for business application
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • patents or publications at top-tier peer-reviewed conferences or journals
  • programming in Java, C++, Python or related language
  • algorithms and data structures
  • parsing
  • numerical optimization
  • data mining
  • parallel and distributed computing
  • high-performance computing

Nice to have

  • supply chain optimization
  • operations research
  • vendor management systems
  • Unix/Linux
  • professional software development

What the JD emphasized

  • agent to agent collaboration
  • humans-in-the loop collaborative methods
  • agentic GenAI workflows
  • end-to-end vendor coaching and evaluation
  • large volumes of data
  • highly complex supply chain contexts
  • deep understanding about machine learning/reinforcement learning/GenAI models
  • diving into data to analyze root causes
  • implementing long term solutions
  • translate complex business logic into scalable models
  • exceptional Science depth and breadth
  • analytics
  • statistics
  • judgment
  • communication skills

Other signals

  • agentic GenAI workflows
  • collaborative inventory planning with vendors through agent to agent collaboration or humans-in-the loop collaborative methods
  • automate the end-to-end vendor coaching and evaluation
  • build high-performance, distributed training and inference pipelines