Applied Scientist, Na Stores Expansion

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

This Applied Scientist role focuses on building and deploying AI/ML models and LLM-powered systems for Amazon's North America Stores. The role involves developing workflows that combine ML models with optimization engines and human-in-the-loop capabilities, building scalable data and inference pipelines, and designing experimentation frameworks. The goal is to automate complex business processes and serve real-time predictions in production, impacting areas like supply chain, customer engagement, and inventory management.

What you'd actually do

  1. Develop workflows that combine ML models with optimization engines, similarity search, and human-in-the-loop capabilities to automate complex business processes
  2. Build scalable data and inference pipelines using AWS services (SageMaker, Bedrock, FAISS, Andes) to process 100M+ ASINs and serve real-time predictions in production
  3. Design and execute rigorous experimentation frameworks including weblabs, IPC labs, and causal inference methods to validate model impact and drive launch decisions
  4. Collaborate cross-functionally with engineering, product, and business teams to translate ambiguous business problems into well-scoped science solutions with clear success metrics

Skills

Required

  • ML models
  • LLM-powered systems
  • optimization engines
  • human-in-the-loop capabilities
  • scalable data pipelines
  • inference pipelines
  • AWS services
  • SageMaker
  • Bedrock
  • FAISS
  • Andes
  • experimentation frameworks
  • weblabs
  • IPC labs
  • causal inference methods
  • Java
  • C++
  • Python
  • algorithms and data structures
  • parsing
  • numerical optimization
  • data mining
  • parallel and distributed computing
  • high-performance computing

Nice to have

  • Unix/Linux
  • professional software development
  • generative AI tools
  • effective prompting
  • evaluation practices
  • prompting
  • evaluation

What the JD emphasized

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

Other signals

  • building and deploying AI / ML models and LLM-powered systems
  • automate complex business processes
  • serve real-time predictions in production
  • translate ambiguous business problems into well-scoped science solutions