Data & Applied Scientist 2 at Microsoft

Data & Applied Scientist 2 Details

Jan. 29, 2019, 4:46 a.m.
Individual Contributor
Bellevue, WA
Microsoft AI and
Our team is part of Microsoft AI and Research working on deep learning to power end user experiences relating to the following four areas: a. Relevance of search results on b. Question-answering system for Bing and Cortana c. Enterprise search for sharepoint and other work related content d. Recommendation system for news feed system The team works on projects across the entire deep learning life-cycle. This includes deep learning models for ranking, summarization, universal representation learning, reinforcement learning, question-answering, user modeling, template free language generation, etc. Apart from this, we also work on improving training performance, run-time optimized inference, distributed training, and other similar aspects. The team works across most of the common modeling scheme like RNNs, CNNs, VAEs, GANs, etc. Most of these models are targeted to serve live user traffic and hence have to be optimized for serving at very tight latency constraints. We use a diverse

As part of the team, you would be driving projects through their entire life-cycle from idea creation through implementation, experimentation and finally shipping to our users. We are looking for strong, motivated, results-oriented applied scientists and software engineers to help drive the design and implementation of the next wave of improvements of products for Bing and Microsoft. You would be working with truly big data by training and extending the capability of deep learning models to provide compelling experiences across our products. Projects can span across modeling, data engineering,
MS/Ph.D. in CS/EE or related areas is required Strong ability and effectiveness working in a significant technical problem domain, in the term of plan, design, execution, continuous release and service operation. Strong software engineering fundamentals, including coding, problem solving and data analysis skills. Background in machine learning/deep learning (strongly preferred). Passionate and self-motivated. Ability to effectively work in collaborative multiple project team environment and ship production features in a fast-paced environment. Good communication skills, both verbal and written
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