Amazon - New York, NY

posted about 1 month ago

Full-time - Mid Level
New York, NY
10,001+ employees
Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Machine Learning Engineer II position in the Monetization team at Amazon focuses on building auction pricing systems for Sponsored Products. This role involves designing and developing scalable software solutions that support both offline machine-learning pipelines and online serving components. The engineer will work collaboratively with scientists and engineers to optimize pricing strategies, enhance machine learning productivity, and ensure a seamless shopping experience for customers while maximizing ad revenue for sellers.

Responsibilities

  • Design, develop, and production software to support scalable offline machine-learning pipelines and online serving components.
  • Partner with scientists to build pricing systems to test auction monetization policies by running A/B experiments.
  • Integrate solutions with high volume and low latency distributed systems.
  • Measure the impact and customer response to solutions through rapid experimentation.
  • Work closely with applied scientists to optimize the performance of machine-learning models and improve the team's machine learning productivity.

Requirements

  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture experience of new and existing systems
  • Experience programming with at least one software programming language
  • Bachelor's degree in computer science or equivalent

Nice-to-haves

  • 3+ years of full software development life cycle experience
  • Master's degree in computer science or equivalent
  • Experience in machine learning, data mining, information retrieval, statistics or natural language processing

Benefits

  • Competitive salary based on market location
  • Equity and sign-on payments
  • Comprehensive medical benefits
  • Financial benefits including retirement plans
  • Diversity and inclusion programs
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