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Software Development Engineer- AWS Machine Learning

Software Development Engineer- AWS Machine Learning

Job ID 
473428
Company/Location (search) 
US-WA-Seattle
Posted Date 
11/13/2017
Company 
Amazon Corporate LLC
Recruiting Team 
North American Teams - AWS

Job Description

Come be part of the Amazon Artificial Intelligence Team! We are a cloud AWS service that helps customers run machine learning and deep learning algorithms in a scalable and cost effective manner. With machine learning, businesses now ask our machines to do more than repetitive, strictly defined tasks. We are taking it one step further and have begun to ask them to not only learn on their own but to interpret data and report to the customer before they even knew they needed it. It's a step in history for you to be a part of. You will be building a platform that incorporates best practices and can run advanced algorithms in production scale and reliability. We are the 'applied' side of the machine learning movement.

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

Basic Qualifications

Bachelor’s or Ph.D degree in Computer Science or equivalent work experience.
· 5+ years professional experience in software development of multi-threaded, scalable and highly-available distributed systems.
· Computer Science fundamentals in object-oriented design, data structures, high-performance computing.
· Computer Science fundamentals in algorithm design, complexity analysis, problem solving and diagnosis.
· Proficiency in, at least, one modern programming language such as Java, Python, C/C++, C#, Perl.

Preferred Qualifications

Experience taking projects from scoping requirements through V1 launch and V2 iterations.
· Knowledge of professional software engineering practices and 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 machine learning, deep learning, data mining, and/or statistical analysis tools.