Senja Filipi
Principal Software Engineering Manager at Microsoft
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolSenja Filipi is a Principal Software Engineering Manager in Seattle with 9 years of focused experience at Microsoft building intelligent user experiences that blend machine learning, software engineering, and UX. She leads an Applied Science and Engineering team shipping ML-driven features in Microsoft Teams such as Speaker Coach and Teams Facilitator, and previously drove ML.NET and cross-platform model tooling in Azure Machine Learning. Her background spans hands-on ML engineering—implementing algorithms like Factorization Machines in the ML.NET open-source repo—to scaling data collection and parameter tuning for production systems. Earlier roles include UX component development across Office 365 and building high-coverage automated test frameworks for high-traffic backend services, showing a rare mix of product-facing UI sensibility and rigorous engineering discipline. She holds an MSc in Computer Science from the University of Washington and a prior MSc and BSc in Computer Engineering, grounding her leadership in strong academic and practical foundations. Colleagues value her ability to translate research-grade ML into polished, user-centric features that ship at scale.
9 years of coding experience
9 years of employment as a software developer
Master of Science (MSc) Computer Science, Master of Science (MSc) Computer Science at University of WashingtonMaster of Science (MSc) Computer Engineering, Master of Science (MSc) Computer Engineering at Universiteti Politeknik i Tiranës
English, Albanian, French, Italian
Github Skills (12)
algorithm10
net10
asp-net10
factoring10
machine-learning10
factors10
2factor10
dotnet10
machine-learning-algorithms10
csharp10
factorization10
dotnet-core10
Programming languages (9)
Github contributions (5)
dotnet/machinelearning
Jun 2018 - May 2019
ML.NET is an open source and cross-platform machine learning framework for .NET.
Role in this project:
ML Engineer
ML EngineerContributions:122 commits, 282 PRs, 117 pushes in 11 months
Contributions summary:Senja implemented Factorization Machines, including the core trainer code within the Microsoft Machine Learning framework. The code differences show the creation of a new file containing the core logic for the Factorization Machine trainer, involving various arguments like learning rate, and regularization, suggesting an understanding of the underlying ML algorithms. The commit messages and code changes indicate a focus on implementing a specific machine learning algorithm within the ML.NET ecosystem.
machine-learning-platformdotnetml-netmachine-learningcsharp
sfilipi/machinelearning-1
Jun 2018 - May 2019
ML.NET is the core library of machine learning in .net.
Contributions:710 pushes, 238 branches in 11 months
dotnetml-netmachinelearningmlmachine-learning
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