Decision trees, feature engineering, deep learning, personalization, web graph analysis, high performance distributed systems, multi-metric joint-optimization, do any of these technologies excite you? Want to work with top talent on this? The Bing Whole Page Revenue Optimization team is a growing team responsible for making major improvements to Bing's revenue and quality. We live and breathe Big Data and Machine Learning. We build and trains state-of-the-art machine-learned models every day to improve the search experience and revenue for Bing. We are responsible for delivering almost 10% improvement to Bing's revenue year over year by optimizing multiple aspects of Bing's search results page. The team owns Bing's revenue optimization end to end, including infrastructure that ranks, triggers or adjusts UX of different features, machine learning models that predict multiple metrics that Bing tracks, offline pipelines that generate required features, diagnostics and reports. As part of the
We are looking for a strong Software Engineer or Applied Scientist to help us continue on our quest to delight users with the experience while improving Bing's revenue. The ideal candidate would have strong practical and theoretical knowledge of machine learning or data mining techniques and also have a proven track record of innovation and shipping high quality changes to production software. You will be asked to take on some big challenges. You'll invest your time in multiple areas: - Research, design and execution of experiments that explore and identify new ways to improve Bing's user experience
2+ years of software engineering experience with a general-purpose programming language (C/C++/C#/Java Etc S., M.S. or PhD in Computer Science or related field Strong algorithmic problem solving and design skill Experience in Machine learning, data mining, statistical analysis and information retrieval techniques Track record of designing, developing, and shipping high performance service Ability to communicate technical concepts effectively through design documents and presentations.