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Do you want to build cutting-edge highly scalable services & infrastructure using AWS technologies and support new machine learning initiatives? Does the prospect of building services serving billions of requests per day while maintaining response latencies in milliseconds and meeting strict SLA requirements, excite you?We are looking for a Software Engineer, who can drive appropriate technology choices for the business, lead the way for continuous innovation, and shape the future of recommendation systems in Amazon Books. You will build services to handle billions of requests per day, while maintaining response latencies in milliseconds and meeting strict SLA requirements. It is quite routine for our systems to operate on massive datasets using distributed frameworks. You will design and code, troubleshoot, and support high volume and low latency distributed systems. You will develop ML models either from scratch or by modifying existing algorithms. The solutions you create would drive step increases in building better recommender and/or helping more customers. You will directly impact our customers’ book shopping experience. This role will provide exposure to cutting-edge innovations in recommender system, as well as working experience on science side of the spectrum.
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- Experience building complex software systems that have been successfully delivered to customers
- 1+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
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