Interested in Machine Learning, and empowering the world to do more and better machine Learning? With Amazon SageMaker, Amazon Web Service's (AWS) Machine Learning platform team is building customer-facing services to catalyze data scientists and software engineers in their machine learning endeavors. This product is a blend of HTTP API's, low and high-level SDK's, and an AWS Console UI. .
As part of the ML Platform Frontend team, you will design, implement, test, document, and deliver the user experiences for our new AWS machine learning services. This can involve innovative UI's and further down the stack at the webserver/API layer. You'll assist in gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture. You will serve as a key technical resource in the full development cycle, from conception to delivery and maintenance. You will produce comprehensive, usable software documentation; recommend changes in development, maintenance and system standards. You will own delivery of entire piece of the system and serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers.
We're moving fast, and this is a great team to come to to have a huge impact on AWS and the world's customers we serve!
Bachelor’s Degree in Computer Science or related field
Computer Science fundamentals in object-oriented design
Computer Science fundamentals in data structures
Computer Science fundamentals in algorithm design, problem solving, and complexity analysis
Proficiency in, at least, one modern programming language such as Java, Python, Scala, C++, or C#.
2+ years professional experience in software development
Experience building complex software systems that have been successfully delivered to customers
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
Ability to take a project from scoping requirements through actual launch of the project
Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs.
Deep hands-on technical expertise in: large scale systems engineering; building and operating complex distributed systems.
Experience with Machine Learning, data mining, and/or statistical analysis tools.
Master's degree in Computer Science, Computer or Electrical Engineering