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Senior Data Scientist/Research Engineer
hace 1 mes
Overview
At Microsoft, we're passionate about innovation and collaboration. Our Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence. Our mission is to build the data platform for the age of AI, powering a new class of data-first applications and driving a data culture.
We're hiring a Senior Applied Scientist for the Gray Systems Lab (GSL), an applied research group part of the Azure Data CTO office. GSL tackles interesting challenges in both open-source and proprietary technologies related to analytics, cloud, AI, and storage systems among others. We build reliable, highly scalable and high-performing distributed systems for data analytics on Azure, we publish in top-conferences and are actively involved in open-source projects.
As a member of our team, you'll work on novel technologies including analytics on GPUs, container technologies, graph databases, infrastructure and models for LLMs and data-science, machine learning for systems, and many other areas. With team members originating from 10 countries and 4 continents, each of us brings something authentically unique to the team. In this diverse and inclusive environment, creativity, open dialogue, and a healthy work-life balance are powering GSL innovation and helping each of us grow.
We're dedicated to empowering every person and every organization on the planet to achieve more, and we're committed to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day.
Key responsibilities include:
- Designing and developing novel technologies for data analytics on Azure
- Collaborating with cross-functional teams to integrate our products into Azure Synapse Analytics
- Publishing research papers in top conferences and contributing to open-source projects
- Working on novel technologies including analytics on GPUs, container technologies, graph databases, infrastructure and models for LLMs and data-science, machine learning for systems, and many other areas
