Software Engineer at Microsoft

Software Engineer Details

Feb. 13, 2019, 3:01 a.m.
Individual Contributor
Bellevue, WA
Ads Relevance team The Bing Ads
Online Advertising is one of the fastest growing businesses on the Internet today - serving millions of ad impressions per day and generating terabytes of user events data every day. The rapid growth of online advertising has created enormous opportunities as well as technical challenges that demand computational intelligence. The Bing Ads Relevance team is at the center stage of this exciting new interdisciplinary field that involves natural language processing, query understanding, machine learning, data mining, and statistics, to solve challenging problems that arise in online advertising. The central problem of computational advertising is to select an optimized slate of relevant ads for a user to maximize a total utility function that captures the expected revenue, user experience and return on investment for advertisers. We are a world-class R and D team of passionate and talented scientists and engineers who aspire to solve tough problems and turn innovative ideas into high-quality

- Building and owning production machine learning models to predict ads relevance. - Finding insights and forming hypothesis on web-scale data with various machine learning, statistical, and data mining techniques: e.g. regression, classification, optimization, p-values analysis. - Designing experiments, understanding the resulting data, and producing actionable, trustworthy conclusions from them. - Wrangling large amounts of data (think petabytes) using various tools, including open-source ones and your own. - Taking complex problems and associated data to arrive at answers in a concise form.
- A graduate degree in computer science or a quantitative domain plus hands-on software engineering and data science experience. Familiarity with C# or C++, SQL, and Python or R is preferred. - 3+ year experience delivering, scaling, and owning highly successful and innovative machine learning products. - Experience with deep learning models (DNN, RNN, LSTM) and frameworks (TensorFlow, Keras, PyTorch, etc.) will be very helpful. - Excellent verbal, visual and written communication skills. - A willingness to learn, share, and improve.
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