Software Development Engineer, Sponsored Products and Brands

Amazon Amazon · Big Tech · Palo Alto, CA · Software Development

Software Development Engineer role focused on building and enhancing large-scale ML training and real-time inference systems for Amazon Ads, with a specific emphasis on pioneering LLM inference infrastructure and optimizing model performance. The role involves designing ML data pipelines and driving operational excellence for model serving systems, directly impacting customer-facing ad relevance.

What you'd actually do

  1. Enhance the scalability, automation, and efficiency of large-scale ML training and real-time inference systems
  2. Pioneer the development of LLM inference infrastructure to support next-generation GenAI workloads at Amazon Ads scale
  3. Work closely with applied scientists to optimize machine learning model performance and implement end-to-end solutions from experimentation through production
  4. Design and build ML data pipelines leveraging techniques in machine learning, data mining, information retrieval, statistics, and NLP
  5. Drive operational excellence for ML infrastructure — monitoring, automation, and continuous improvement of model serving systems

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
  • Experience in machine learning, data mining, information retrieval, statistics or natural language processing

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

  • large-scale ML training and real-time inference systems
  • LLM inference infrastructure
  • optimize model performance at scale
  • ML data pipelines
  • model serving systems

Other signals

  • ML training and real-time inference systems
  • LLM inference infrastructure
  • optimize model performance at scale
  • ML data pipelines
  • model serving systems