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Principal Software Engineer (Big Data)
3 years ago

Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers to levels they cannot achieve anywhere else. This is a world of more possibilities, more innovation, more openness, and the sky is the limit thinking a cloud-enabled world. 

 

Microsoft’s Intelligence Platform engineering team is leading the transformation of analytics in the world of data with products like Power BI, Synapse Analytics, Azure Data Factory, Azure Data Explorer. We will bring the world’s data to the Microsoft Cloud, power a new class of data first applications, and empower everyone on the planet to make better decisions with data.   

 

We do not just value differences or different perspectives. We seek them out and invite them in so we can tap into the collective power of everyone in the company. As a result, our ideas are better, our products are better, and our customers are better served. 

At the core of the AI revolution lies data: Machine learning is used to create software artifacts from data. This data is valuable and requires careful management. Azure Data is the world leader in data management and processing with products such as SQL Server, Azure HDInsight, and Azure Synapse.

We are expanding our team to bring together the best in big data management and machine learning. We work with and contribute to state-of-the-art open-source packages, including Apache Spark, Koalas, Pandas, Dask, sklearn, MLFlow, TensorFlow, and PyTorch. We combine those with our own tech to build secure, dependable, scalable, and high-performance machine learning platforms. With our platforms, we strive to enable our customers to follow the principles of responsible AI: Fairness, Inclusiveness, Reliability & Safety, Privacy & Security, Transparency, Accountability.

To support these ambitions, we are growing our distributed team across multiple locations. We also collaborate closely with teams across Microsoft, including Microsoft Research, Azure ML, and our own Gray Systems Lab. We strive for an open, collaborative environment where equal participation from every location is possible. To do so, we apply best practices from open-source development to our own work style. 

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