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We seek a Principal Researcher with expertise in query execution, data storage, resource management for serverless cloud platforms, data discovery, and data preparation techniques. Candidates with experience in leveraging novel hardware, Artificial Intelligence (AI), and Machine Learning (ML) for data management challenges are of special interest to us. Our past research has been incorporated into Microsoft’s products and services such as SQL Server, Azure SQL Database, Power BI, Excel, and Dynamics 365. We have had influential publications at top conferences such as ACM SIGMOD, VLDB, and IEEE ICDE including several best paper awards and test-of-time awards.
Job Responsibility:
Pursue high-ambition research on data systems in collaboration with other members of the research lab
Build and deploy novel systems
Contribute significant innovations to Microsoft’s products and services
Publish papers on significant research results
Embody our culture and values
Requirements:
Doctorate in Computer Science, Computer Engineering, or relevant field AND 3+ years related research experience OR equivalent experience
A track record of research accomplishments, e.g., major conference publications (ACM SIGMOD, VLDB)
Expertise in query execution, data storage, resource management for serverless cloud platforms, data discovery, and data preparation techniques
Experience in leveraging novel hardware, Artificial Intelligence (AI), and Machine Learning (ML) for data management challenges
Nice to have:
Doctorate in relevant field AND 5+ years related research experience OR equivalent experience
Experience publishing academic papers as a lead author or essential contributor
Appetite for undertaking ambitious research challenges
Familiarity with traditional SQL or big data systems cloud platforms
Expertise in key components of data systems, e.g., distributed query execution, resource management for cloud platforms, low-code data transformations
In-depth knowledge of modern hardware
Experience with applying AI and Machine Learning techniques for challenges in data systems