Machine Learning Engineer, Aice - AI Center of Excellence

Amazon Amazon · Big Tech · CA, BC +1 · Software Development

Machine Learning Engineer at Amazon's AI Center of Excellence (AICE) responsible for the end-to-end development and deployment of AI/ML primitives that power Amazon's intelligent systems. This role involves ideation, experimentation, architecture, implementation, testing, and production deployment of reusable AI capabilities for enterprise-wide consumption, with a focus on reliability, scalability, and operational excellence.

What you'd actually do

  1. Own the end-to-end development of AI/ML primitives - from ideation and experimentation through architecture, implementation, testing, and production deployment
  2. Drive the integration of AICE primitives into partner products, collaborating closely with product-owning teams to ensure seamless adoption and value delivery
  3. Design, test, and harden primitives for general availability, enabling consumption by other teams and product owners across the organization
  4. Architect solutions suitable for production environments, maintaining best practices in reliability, scalability, observability, and operational excellence
  5. Contribute to AICE's mission of driving AI transformation through best practices in AI-driven development, implementation processes, and operationalization within your area of expertise

Skills

Required

  • Experience programming with at least one software programming language
  • Bachelor's degree or above in computer science
  • Experience leading design teams in problem definition, artifact rendering, cross-functional collaboration and delivery, and user validation and measurement
  • 2+ years of non-internship professional software development experience
  • 1+ years of experience designing or architecting systems (design patterns, reliability, and scaling) for production AI/ML workloads
  • 1+ years of experience building, hardening, and operationalizing AI/ML solutions - from experimentation through production deployment
  • Strong foundation in traditional software development practices (code reviews, testing, debugging, version control, CI/CD) with the ability to also leverage AI-assisted development tools effectively
  • Experience building reusable libraries, frameworks, or platform capabilities consumed by other engineering teams

Nice to have

  • 2+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Master's degree in computer science or equivalent
  • Experience in machine learning, data mining, information retrieval, statistics or natural language processing

What the JD emphasized

  • production AI/ML workloads
  • building, hardening, and operationalizing AI/ML solutions
  • reusable libraries, frameworks, or platform capabilities

Other signals

  • end-to-end development of AI/ML primitives
  • integration of AICE primitives into partner products
  • architect solutions suitable for production environments
  • building reusable libraries, frameworks, or platform capabilities