Come and be part of the Amazon AI team! We are a cloud AWS service that helps customers run machine learning algorithms on various Big Data systems in a scalable and cost-effective manner. With AWS AI, 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 also 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 runs advanced algorithms at production scale and reliability. In this role, you will be responsible for architecting, implementing and expanding features, services and core components for our AWS services. 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.
Bachelor’s or Ph.D degree in Computer Science or equivalent work experience. · 7+ 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.
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 experimentation and statistics. · Experience with machine learning, deep learning, data mining.