The Amazon Prime Video Recommendations team mission is to make it effortless for every customer to find their next favorite movie or TV show. The team is seeking a talented and passionate Software Development Engineer interested in applying Machine Learning to power personalized recommendations for Amazon Instant Video customers globally. You will work as part of a team of stellar software engineers and researchers to experiment with rich video datasets and innovative algorithms to deliver a compelling lean back entertainment experience for millions of customers. We’re building the future of TV—yes, it’s challenging, but it’s also a lot of fun.
A successful candidate will have an established background in developing customer-facing experiences, a strong technical ability, great communication skills, a motivation to achieve results in a fast-paced environment, high creativity, great analytical reasoning skills, and, of course, a passion for TV and movies.
· 2+ years of non-internship professional software development experience
· Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
· 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
· Meets/exceeds Amazon’s leadership principles requirements for this role
· Meets/exceeds Amazon’s functional/technical depth and complexity for this role
· Master's Degree in Computer Science or related field.
· Experience building machine learning models and online services
· Experience with 24x7 systems
· Experience with high throughput, multi-threaded systems
· Experience with Java
· Excellence in technical communications with both technical and non-technical peers
· 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
Amazon is an Equal Opportunity Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / Age