Zeeshan Ahmed
Research Scientist (GenAI) at Meta
Redmond, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolZeeshan Ahmed is a Research Scientist specializing in Generative AI with eight years of experience building and deploying state-of-the-art ML solutions across speech, NLP, and large language models. Currently at Meta, he brings a rare mix of academic rigor—PhD-level training in Machine Learning and NLP from University College Dublin—and industry impact from roles at Microsoft Research and Amazon focused on conversational ASR and applied AI. He is an active reviewer and program committee member for top conferences (ACL, EMNLP, ICASSP, Interspeech), signaling deep engagement with the research community and emerging trends. Zeeshan also contributes to prominent open-source projects in the .NET ML ecosystem, improving ML.NET and TensorFlowSharp with testing, optimizer implementations, and string-tensor support—work that highlights both systems-level engineering and practical ML tooling. Known for translating research into robust production features, he combines strong debugging/testing instincts with a track record of improving developer experience (IntelliSense and test suites) in cross-platform ML libraries.
8 years of coding experience
8 years of employment as a software developer
Master of Science (MS) - 2nd Year, Computer Science (NLP), Master of Science (MS) - 2nd Year, Computer Science (NLP) at Universite de LorraineDoctor of Philosophy (Ph.D.), Machine Learning and NLP, Doctor of Philosophy (Ph.D.), Machine Learning and NLP at University College DublinMaster of Science (MS) - 1st Year, Computer Science ( NLP), Master of Science (MS) - 1st Year, Computer Science ( NLP) at Charles University
Github Skills (14)
testing10
net10
asp-net10
machine-learning10
dotnet10
refactoring10
tensorflow10
mlnet10
csharp10
mldotnet10
dotnet-core10
sgd9
algorithms9
unit-testing8
Programming languages (4)
Github contributions (5)
dotnet/machinelearning
May 2018 - May 2019
ML.NET is an open source and cross-platform machine learning framework for .NET.
Role in this project:
Backend & ML Engineer
Backend & ML EngineerContributions:66 commits, 128 PRs, 55 pushes in 1 year
Contributions summary:Zeeshan contributed to refactoring scenario tests and implementing improvements to the existing tests within the ML.NET framework. They modified several test files, including those related to house price prediction, sentiment prediction, and iris plant classification, demonstrating expertise in testing and refactoring. Further contributions included adding comments to the LearningPipeline class to improve Intellisense and addressing issues with exception handling, indicating involvement in both backend development and debugging/testing.
machine-learning-platformdotnetml-netmachine-learningcsharp
migueldeicaza/TensorFlowSharp
Feb 2019 - Oct 2019
TensorFlow API for .NET languages
Role in this project:ML Engineer
ML EngineerContributions:7 commits, 9 PRs, 2 comments in 8 months
Contributions summary:Zeeshan significantly contributed to the TensorFlowSharp library by implementing and testing features for string tensor input and output, as well as adding optimizers such as Adagrad and RMSProp. They also added support for training using Stochastic Gradient Descent (SGD) with momentum and Nesterov. These changes included the creation of new tests and modifications to existing ones to ensure the correct functionality of the updated optimization algorithms and string data handling.
apidotnetdot-netnet-languagesmono
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