PRINCIPAL SOFTWARE ENGINEER at Microsoft

PRINCIPAL SOFTWARE ENGINEER Details

April 30, 2019, 2:36 a.m.
Engineering
Individual Contributor
Full-Time
Bellevue, WA
AI Infrastructure team Artificial Intelligence as
Microsoft bets on Artificial Intelligence as the next growth opportunity for the company. Bing, Cortana, Office 365 and MS Research are in the forefront in applying Deep Learning to Natural Language Processing, Speech and Image recognition. The AI Infrastructure team is delivering next generation Deep Learning infrastructure, to the world, so that data scientists can enrich their target customers experience with the magic of AI. As a team, we adopt a culture of meritocracy, bias towards taking big risks and failing fast, and value hacking together. You will join a team of talented engineers who love solving hard problems, embrace open source and actively participate and contribute back to Open Source communities. If you are a hard-core developer who is passionate about Infrastructure development, you should join us.

As part of the core team, you will be leading a group of engineers who are currently working on simplifying the data science process for AzureML that allows our customers to run model training jobs over 100s of GPUs on Azure. You will contribute to the design and implementation of the core Azure AI Training Service , We value passion, creativity, and desire to learn new complex technical areas, agility and accountability while pivoting a team towards greater result. We are looking for motivated, result-oriented and collaborative people who have a drive for results. As a leader of the team, you
Minimum of 5+ years of Management experience required. A minimum of a Bachelor's degree in Computer Science or Engineering, or a related field, or equivalent alternative education, skills, and/or practical experience is required. Expertise in C#, Java, Scala, C++ or Python Experience with distributed systems design and implementation, especially microservices architecture, and experience with cluster scheduling technologies like Hadoop Yarn, Kubernetes, Fleet, etc is a plus.
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