Software Dev Engineer, Applied AI

Amazon Amazon · Big Tech · Bellevue, WA · Software Development

Software Development Engineer II (SDEII) on the Applied AI team, focusing on LLM-based solutions to accelerate knowledge operations and scale inputs for the eCommerce business. Responsibilities include developing and maintaining systems and tools, working at the intersection of Science and Engineering, and pushing boundaries of ML and Generative AI techniques. Requires experience in Python, Java, container-based development, SageMaker, PyTorch, PyTorch Lightning, and Langchain.

What you'd actually do

  1. developing and maintaining the systems and tools that enable us to accelerate knowledge operations and work in the intersection of Science and Engineering
  2. push the boundaries of ML and Generative AI techniques to scale the inputs for hundreds of billions of dollars of annual revenue for our eCommerce business
  3. learn, and be ready to use a wide range of software and development tools required to perform the job in Python, Java, container-based development, SageMaker, PyTorch, PyTorch Lightning, Langchain, etc.
  4. help the team evolve by actively participating in the code review process, design discussions, and team planning
  5. participate in all projects in the functional area by helping to review designs, contributing to code reviews, and helping to remove blockers

Skills

Required

  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language
  • Python
  • Java
  • container-based development
  • SageMaker
  • PyTorch
  • PyTorch Lightning
  • Langchain

Nice to have

  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent

What the JD emphasized

  • LLM-based solutions
  • ML and Generative AI techniques

Other signals

  • LLM-based solutions
  • scale the inputs for hundreds of billions of dollars of annual revenue
  • accelerate knowledge operations