Software Engineer Ii, Prime Turing

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

Software Engineer II role focused on building and scaling machine learning infrastructure for Prime Turing, which handles over 350 billion events annually for customer lifecycle orchestration. The role involves designing and implementing scalable, fault-tolerant distributed systems for predictions and serving ML models, with a focus on recommendation, ranking, personalization, or search experiences.

What you'd actually do

  1. Design and build innovative technologies in a large distributed computing environment and help lead fundamental changes in the industry.
  2. Create solutions to run predictions on distributed systems with exposure to innovative technologies at incredible scale and speed.
  3. Build distributed storage, index, and query systems that are scalable, fault-tolerant, low cost, and easy to manage/use.
  4. Design and code the right solutions starting with broadly defined problems.

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

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
  • 2+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
  • Experience in machine learning, data mining, information retrieval, statistics or natural language processing
  • Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems, or experience designing or architecting (design patterns, reliability and scaling) of new and existing systems

What the JD emphasized

  • building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
  • Experience in machine learning, data mining, information retrieval, statistics or natural language processing

Other signals

  • building large-scale machine-learning infrastructure
  • online recommendation, ads ranking, personalization or search experience
  • machine learning, data mining, information retrieval, statistics or natural language processing