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Software Development Engineer II, AWS Machine Learning Service

Software Development Engineer II, AWS Machine Learning Service

Job ID 
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Posted Date 
Amazon Corporate LLC
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Job Description

Interested in engineering world's best Machine Learning service on AWS? Join us to make Amazon the best place in the world to do ML.
You will be working to build large scale system from the ground up to execute ML jobs. Our mission is to facilitate productionalization of Machine Learning models easier for different classes of users ranging from ML experts to developers without ML knowledge.
Amazon's machine learning platform team currently supports services inside of the company and the AWS service AmazonML. Please take a look at
You will work in the company of world experts and there are immense learning as well as growth opportunities.

In this role you will design, implement, test, write library code and own a SOA-based platform using object-oriented, distributed programming, Java, other AWS services and more in Linux environment. You will do everything from determining priorities and designing features to re-architecture as necessary, automated testing and mentoring others. The best candidates show true end-to-end ownership.

Basic Qualifications

  • Bachelor’s Degree in Computer Science or related field or equivalent work experience
  • 3+ years professional experience in software development
  • Strong computer science fundamentals - data structures, algorithms design, complexity analysis, operating systems etc.
  • Object-oriented design
  • Strong analytical abilities and problem solving
  • Strong inclination towards building high quality systems by testing mercilessly.
  • Strong sense of ownership and willing to own end to end systems.
  • Proficiency in, at least, one modern programming language such as Java, Python, Scala, C++, C#.

Preferred Qualifications

  • Experience taking projects from scoping requirements through V1 launch and V2 iterations.
  • Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
  • Experience with highly distributed, multi-tenet systems with clear state-full/state-less boundaries.
  • Experience with experimentation and statistics.
  • Experience with machine learning, data mining tools and techniques