Senior Applied ML Scientist at Microsoft

Senior Applied ML Scientist Details

May 20, 2019, 7:35 p.m.
Engineering
Individual Contributor
Full-Time
Redmond, WA
Machine Learning team Data? Do you
Do you have a passion for Data? Do you dream of working with customers on their most forward looking AI initiatives? Are you interested in natural language processing or information retrieval? Does the challenge of developing modern machine learning solutions to solve real-world business problems sound exciting to you? If you answered "yes" to these questions, we want to talk to you about joining the CSE Machine Learning team. We are a group that engages partners in all corners of the world and work alongside them to build a new breed of intelligent solutions and systems. We are looking for an Applied Machine Learning Scientist with strong analytical and development skills to join our expanding team. The most successful candidates will have several years of real-world experience building production ML/AI systems and applying machine learning algorithms across a breadth of modern technology platforms. They are customer focused and practical, enjoy challenging projects and have strong analytical

• Developing and deploying solutions with Microsoft Partners for solving business problems using machine (deep) learning and predictive modeling techniques; • End-to-end execution of the data science process, from understanding business requirements, data discovery and extraction, model development and evaluation, to production pipeline implementation. • Building production level ML/AI solutions, with solid software engineering and ML/AI principles. • Providing technical subject matter expertise in OSS and Microsoft big data technologies, to develop technical content in support of developer events,
• MS/PhD in Computer Science, EE, Statistics, Computational Linguistics or equivalent technical field. • 5+ years of solid understanding of common statistical and machine learning techniques, both classical machine learning and deep learning. • 5+ experience with end-to-end ML implementation, including data pre-processing, feature engineering and tuning of ML models during training and in production. • Broad ML experience across a variety of applications, but a deeper expertise in one or more topics (text, vision, structured data). • Working knowledge and/or interest in natural language processing
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