Applied Machine Learning Scientist
Bellevue, Washington, United States
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Overview
Microsoft's mission is to empower every person and every organization on the planet to achieve more and we believe that artificial intelligence will play a critical role in accomplishing that mission. The Core Search and AI team is the leading applied machine learning team at Microsoft responsible for delivering the highest-quality experience to over 500M+ monthly active users around the world in Microsoft’s search engine, Bing. Beyond Bing other search engines such as Yahoo, DuckDuckGo, and new startups like Neeva depend on us as well.
We have seen little innovation in search in the last decade and we are looking for people who want to build the next generation of search using advanced AI technologies such as deep learning. Our work spans a very large scope of scenarios including delivering high quality search results from a massive document corpus, extractive and abstractive summarization to generate document snippets, personalization, machine reading comprehension, and document recommendations.
As a team, we leverage the diverse backgrounds and experiences of passionate engineers, scientists, and program managers to help us realize our goal of making the world smarter and more productive. We believe great products are built by inclusive teams of customer-obsessed individuals who trust each other and work closely together. We collaborate regularly across the company both to find the technology breakthroughs from groups like Microsoft Research to infusing AI into the rest of Microsoft products like Office and Azure.
Some examples of our work include:
- Developing a massive sparse neural network to improve search relevance (covered by SiliconAngle, Search Engine Land, Venture Beat)
- Building the world’s most comprehensive spelling correction system through zero shot learning (covered by NextWeb, Venture Beat, and ZDNet)
- Using transformer networks for search (covered in Search Engine Land and in State of AI 2020 report)
- Deep learning based question answering and captions (covered in VentureBeat, Search Engine Land)
- Co-developing our large scale training library called DeepSpeed (covered in SiliconAngle, The Batch)
- Open sourcing our vector search algorithm (covered by Ars Technica and TechCrunch)
If you are passionate about working on the latest and hottest areas that will help you develop skills in Artificial Intelligence, Machine Learning, data science and high scale systems, this is the team you’re looking for!
#semanticsearch#
Qualifications
Required Qualifications:
- Bachelors, Masters or advanced degree in Computer Science or related field (including Mathematics and Physics)
- Experience applying Machine Learning techniques
- 2+ years of experience coding in Python, C++, C#, C or Java
Preferred Qualifications:
- MS or PhD computer science or related field.
- Experience with machine learning frameworks such as TensorFlow or PyTorch
- Experience building large scale cloud-based solutions.
- Customer focused, strategic, drives for results, is self-motivated, and has a propensity for action.
- Fantastic problem solver: ability to solve problems that the world has not solved before.
#Search# #WebXT# //s+djobs
Responsibilities
Apply machine learning algorithms to improve search and recommendation systems.
Work on the full lifecycle of machine learning development including training data collection, feature engineering, model training, offline and online experimentation.
Implement the state-of-the-art machine learning algorithms and apply to real production end to end.
Work with tech leads on challenging machine learning projects to deliver product quality improvements.
