- Seattle, WA
Amazon Web Services (AWS) is the leading provider of cloud computing services in the world, offering a broad range of highly reliable, scalable, low-cost cloud services across over 190 countries. AWS infrastructure powers hundreds of thousands of enterprise, government and start-up businesses, including industry leaders such as Amazon.com, Netflix, Expedia, Airbnb, and many more, and renowned organizations such as NASA, the Centers for Disease Control and Prevention (CDC) and Coursera. Though already very successful AWS continues to be a high-growth, fast-moving division within Amazon with a start-up mentality where new and diverse challenges arise every day.
The AWS Central Economics team includes experts in the area of forecasting, causal inference and machine learning and applies economic theory and econometric analysis to build models, systems and tools that inform critical decisions for the AWS business.
As an applied scientist, you will invent, build and deploy state of the art machine-learning models and systems to enable and enhance the team's mission. You will develop a long-term scientific agenda, initiate and lead scientific projects and mentor scientists. You will present your work to product and engineering teams at AWS, publish scientific papers and apply for patents for your inventions.
• Advance exploratory research projects in machine learning and related fields to create highly innovative customer experiences
• Analyze large amounts of data to discover patterns, find opportunities, and develop highly innovative, scalable algorithms to seize these opportunities
• Validate models via statistically rigorous experiments
• Work closely with software engineering teams to build scalable prototypes for testing, and integrate successful models and algorithms in production systems at very large scale
• A Master's or PhD in Computer Science, Mathematics, Statistics, Physics or another quantitative field
• Strong technical credentials, with at least 2 years of professional or post-doctoral experience working in a relevant field: machine learning, deep learning, knowledge bases, recommendation systems, information retrieval, natural language understanding, robotics, statistics, computer vision etc.
• Significant peer-reviewed scientific contributions in premier journals and conferences
• Solid fundamentals in problem solving, algorithm design, complexity analysis, mathematics and statistics.
• Proficiency in a major programming language (Python, Java, Scala or similar).
• Proven track record in leading scientific projects and mentoring scientists;
• Practical experience with big-data processing libraries, eg. Apache Spark, Apache Beam, Apache Pig, Hadoop or similar
• Practical experience with building and evaluating deep-learning models using major libraries eg: mxNet, TensorFlow, Keras or similar
• Proven track record of production achievements, handling gigabyte and terabyte-size datasets
• Experience in defining research vision and getting buy-in from senior research and business leader across the company
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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