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DESCRIPTION
Job summaryAWS Fraud Prevention has opportunities for Software Development Engineers who want to challenge themselves by building solutions using the latest tech in distributed systems at scale to catch the bad actors who are out there. We are at the forefront of protecting AWS (i.e. all AWS services) and its customers from fraud and compromise attacks. Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable and low-cost infrastructure platform in the cloud. As AWS continues to grow at a rapid rate, fraudsters continue to find new ways to exploit our services. We are building evaluation platforms that are extensible, configurable and massively scalable. You will work closely with machine learning research scientists to design next generation fraud and compromise prevention systems utilizing the state of the art in machine learning, streaming data processing and aggregation, graph databases and serverless solutions. Your work will have a direct impact on AWS cloud products and all our customers. You will work in a quickly evolving environment in a business that needs to rapidly adapt to changing fraud patterns.Our low operational load combined with complicated technical and business problems will provide opportunities to satisfy your curiosity and support professional growth.The ideal candidate will have strong distributed systems and web services design and implementation experience, as well as experience working on high availability production systems.About Us Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life Balance Our team puts a high value on work-live balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. Learn more about Amazon on our Day 1 Blog: https://blog.aboutamazon.com/" BASIC QUALIFICATIONS- 1+ years of experience contributing to the system design or architecture (architecture, design patterns, reliability and scaling) of new and current systems.
- 2+ years of non-internship professional software development experience
- Programming experience with at least one software programming language.
- Bachelor's Degree in Computer Science or related field
- 3+ years of commercial software development experience
- Fluency in object-oriented design patterns and languages like Java
- Experience building and operating mission critical cloud software services and an understanding of design for scalability, performance, and reliability
- Ability to work in a fast-paced environment with fluctuating priorities and deadlines
- Ability to solve difficult and highly ambiguous software problems
- Interest and desire to learn new skills and do things truly innovative
- Able to work in a diverse team
- Graduate (Ms) in Computer Science or related field
- Design and architecture experience, preferably of RESTful web services
- Working knowledge of applied machine learning
- Knowledge of XHTML, JavaScript, CSS, and modern web technologies
- Experience with Hadoop, MapReduce, Spark or other big data processing systems
- Experience with payment processing, compliance, or fraud prevention
- Machine Learning a plus
Vacancy expired!