Software Development Engineer - Machine Learning, Big Data, Scale

US-WA-Seattle
2 weeks ago
Job ID
551358
Amazon Corporate LLC
Position Category
Software Development

Job Description

Interested in a new team involving data sciences, algorithm development (machine learning, natural language processing) and an opportunity to impact every Amazon customer?

The newly formed Reconciliation team is responsible for the critical services that assemble the product detail pages on the Amazon website by combining data from sellers, vendors or internal systems, in real-time, millions of times a day. These services, which are a core part of the Amazon's catalog, are being re-built from scratch. The team offers a unique blend of hard computer science problems (scalable distributed systems and high performance algorithms) and an opportunity to help the businesses model their vision on the platform.

Successful candidates are passionate about translating high-level, ambiguous business goals to software platforms that enable multiple businesses. You are comfortable taking initiative and working alongside and leading top-notch software developers.

Basic Qualifications


  • Strong computer science background. A Bachelor's degree or higher in computer science or math or in relevant field.
  • 5+ years of work experience in software development
  • Solid design and coding skills in Java.
  • Strong desire to build high-performance, highly-available, low-cost and scalable distributed systems.
  • Solid communication skills and ability to work well in a team are critical.
  • Highly innovative, flexible and self-directed.

Preferred Qualifications

  • Prior experience leading the development and operation of large scale distributed systems is a plus.
  • Experience solving significant customer problems with Machine Learning and/or Natural Language Processing algorithms.
  • Ability to handle multiple competing priorities in fast paced environment.

Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
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