Software Development Engineer, Core Services

Amazon Amazon · Big Tech · Tempe, AZ · Software Development

Software Development Engineer role focused on building and operating large-scale machine learning systems for fraud detection and risk prevention at Amazon. The role involves developing ML systems for data, feature, model, and rule management, collaborating with ML scientists, and delivering next-gen solutions.

What you'd actually do

  1. Develop large scale, high performance, high reliability ML systems for data, feature, model and rule management.
  2. Work closely with ML scientists, understand the requirements, design and deliver innovative next-gen solutions to help preserve customer trust.
  3. Work as the owner of the system and operate excellent to provide stable and robust services to customers and other teams.
  4. Innovate based on new ideas and build comprehensive system/features across the whole ML pipeline

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
  • 1+ years of software development engineer or related occupational experience
  • 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
  • 1+ years of Object Oriented Design experience
  • Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
  • Experience programming with at least one software programming language

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

  • high judgment decisions
  • high scale
  • machine learning
  • graph modeling techniques
  • highly available and scalable distributed systems
  • production ready relationship data insights
  • large scale, high performance, high reliability ML systems
  • innovative next-gen solutions
  • comprehensive system/features across the whole ML pipeline

Other signals

  • machine learning
  • graph modeling
  • large scale systems
  • fraud detection
  • risk prevention