Sr. Mle, Prime Video - Personalization and Discovery

Amazon Amazon · Big Tech · Sunnyvale, CA · Software Development

Senior Machine Learning Engineer role at Amazon Prime Video focused on developing and launching AI solutions for recommendation and personalization systems. The role involves end-to-end ownership of ML models, including design, implementation, experimentation (A/B testing), and deployment for millions of customers. It requires experience with large-scale ML systems and recommendation systems.

What you'd actually do

  1. Develop AI solutions for various Prime Video Recommendation and Personalization systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods
  2. Work closely with applied scientists, engineers and product managers to design, implement and launch AI solutions end-to-end
  3. Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses
  4. Effectively communicate technical and non-technical ideas with teammates and stakeholders
  5. Stay up-to-date with advancements and the latest modeling techniques in the field

Skills

Required

  • 5+ years of non-internship professional software development experience
  • 5+ years of programming with at least one software programming language experience
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience as a mentor, tech lead or leading an engineering team
  • Experience with large scale machine learning system or application

Nice to have

  • Experience with building large scale recommendation system

What the JD emphasized

  • end-to-end ownership
  • building and guiding machine learning models from the ground up
  • large scale machine learning system
  • building large scale recommendation system

Other signals

  • Develop AI solutions for various Prime Video Recommendation and Personalization systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods
  • Work closely with applied scientists, engineers and product managers to design, implement and launch AI solutions end-to-end
  • Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses
  • Experience with large scale machine learning system or application
  • Experience with building large scale recommendation system