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Amazon Corporate LLC ML Services Software Development Engineer - QuickSight Q in Seattle, Washington

The Amazon QuickSight team is looking for an ML Services Engineer to lead a variety of design and implementation efforts for the QuickSight Q Machine Learning-based Query Pipeline. We are looking for someone who has experience to working alongside data scientist to put machine learning into production. As a Quicksight Q Query Pipeline engineer, you will be be working of the central backbone of the Quicksight Q service, and you will need to develop both a breadth of understanding around how the Q service works as a whole, as well of a depth of experience in how the QuickSight services interacts with deep-learning based NLP models into production, all while contributing to one of the world's most groundbreaking natural language understanding projects.More about Q: Q is a machine learning-powered natural language capability that empowers business users to ask questions about all of their data using everyday business language and get answers in seconds. For example, users simply type "what is our year-over-year growth rate" and get an instant answer in QuickSight as a visualization.More about QuickSight: Amazon QuickSight is revolutionizing Business Intelligence by empowering anyone to use the power of machine learning and Amazon AI to enhance their understanding of data. QuickSight can already help discover hidden insights using Anomaly Detection, enable ML-powered forecasting, and use automatic text generation generate business narratives directly from the data. But we're not stopping here, we remain with helping our customers harness the power of artificial intelligence to help them understand and visualize their data.Inclusive Team CultureHere 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 BalanceOur team puts a high value on work-life 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 GrowthOur 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.* 5+ years of software development experience in Java, C++, C# etc.* 2+ years working alongside science teams to deliver Machine Learning-based systems into production.* Excellent verbal and written communication skills* Strong analytical skills with excellent problem solving* Strong knowledge of data structures, algorithms, OS and distributed systems.* Proven track record of delivery* Experience delivering and operating large scale, highly available distributed systems.* Experience with database systems, query optimization, and storage systems.* Understanding of system performance and scaling.* Possess excellent communication, sharp analytical abilities, and proven design skills.* Masters or PhD in

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