Software Development Engineer II

Description

Do you want to impact the way customers shop at Amazon? Do you want to use Amazon's massive data sets and Machine Learning to do it? Are you an engineer that's not afraid to tackle difficult and ambiguous problems, drive experimentation, and following through to deliver results to customers and our business? We

We are looking for a strong software engineer to join a growing Machine Learning team and help drive our roadmap to explore untapped opportunities across all phases of the Amazon shopping journey. We will look at a wide variety of datasets covering personalization, usage, customer reviews, catalog, contextual purchase behavior, etc, to drive automated product insights, recommendations, offer optimizations and more. Amazon has incredible selection, convenience, and value, but customers don't shop for a TV or a laptop the same way they shop for a new phone case or a book. Using data to help us refine and optimize these experiences is your goal. You will know how and when to invent and build versus collaborate and extend the work of core platforms. In addition to delivering on key projects within the HL-ML team, you will contribute to building and leading a broader ML community across our tech organization spanning 10+ teams focused on a number of $1B+ retail programs and opportunities.

More About the role:

We need an experienced Software Development Engineer to help accelerate end to end delivery of innovative shopping experiences for Amazon.com customers driven by Machine Learning. You will deliver on full stack software development, quality, and operations of features and infrastructure within Amazon.com. You will work with other developers and applied scientists as well as with product managers to guide technical strategy, shape requirements and timelines as well as deliver from development through to launch and operations. You are able to understand business goals and turn them into software that provides innovative value to customers.

More About Us:

CETech is a high-powered and broadly skilled engineering organization responsible for platforms and end-to-end experiences in Amazon retail. The team starts with the challenges facing one of the largest businesses at Amazon, Consumer Electronics, but builds for retail-wide and globally where appropriate. Our work engages the full stack of technology that runs Amazon.com, one of the largest eCommerce engines in the world. We aim to provide the best customer experience through innovative and streamlined shopping and purchase flows that integration with search, payment processing, promotions and marketing, and many other technologies.

Basic Qualifications

  • Bachelor's degree and/or Master's degree in Computer Science or equivalent.
  • 3+ years of software development experience, including Java and/or C++.
  • Computer Science fundamentals in object-oriented design, design patterns, data structures, algorithm design, problem solving, and complexity analysis
  • Knowledge of the following: service-oriented architecture, eCommerce systems, distributed systems design, one or more data processing or analytics technologies
  • Some familiarity or exposure to Machine Learning or Statistical Methods used for prediction, classification, optimization, etc. is desirable
  • Ability to communicate effectively with both technical and non-technical individuals
  • Excellent oral and written communication skills
  • Track record for being detail-oriented with a demonstrated ability to self-motivate and follow-through on projects

Preferred Qualifications

  • Master's degree in computer science or related field
  • Deal well with ambiguous/undefined problems; ability to think abstractly
  • Ability to effectively articulate technical challenges and solutions
  • Experience building scalable, distributed data processing or analytics systems, including one or more technologies such as Spark/EMR, Elasticsearch, AWS Athena, Quicksight, or similar
  • Experience with Machine Learning approaches and technology, for example Deep Learning, Statistical Methods, MXNet, Scikit, SparkML, TensorFlow, R, etc.
  • Experience delivering production systems involving Machine Learning

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