Michael Santacroce
Member Of Technical Staff at Microsoft AI
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolMichael Santacroce is a Member of Technical Staff at Microsoft specializing in full-stack large language model development, spanning data selection, training, and evaluation. With eight years of experience, he blends applied research and software engineering—having led model safety efforts for GitHub Copilot Chat, co-led Phi-Silica work, and contributed to Phi-2/3 pre- and post-training pipelines. He builds practical systems at scale, from Kubernetes-backed provisioning clusters that cut user wait time and cost to tiny on-device classifiers under 400M parameters for safety filtering. His research background includes novel contributions to infinite-width neural network limits, pruning, and efficient RLHF methods like Hydra-RLHF and the GUM fine-pruning technique. Based in Seattle, he pairs deep interests in AI, applied mathematics, compiler and controls theory with a track record of turning research ideas into production-ready tools and benchmarks. He’s open to technical conversations and can be reached directly for resumes or detailed discussions.
8 years of coding experience
6 years of employment as a software developer
Bachelor's of Computer Engineering Master's of Science in Computer Engineering Computer Engineering, Bachelor's of Computer Engineering Master's of Science in Computer Engineering Computer Engineering at University of Cincinnati
Github Skills (27)
python9
machine-learning9
deep-learning9
tensorflow8
neural-network8
recurrent7
data-science7
ml7
deep-neural-networks7
feedforward7
gaussian6
keras6
pruning6
theano6
recurrent-neural-networks6
Programming languages (5)
Github contributions (5)
santacml/nn_pruning
Dec 2021 - Jan 2022
Prune a model while finetuning or training.
Contributions:1 PR, 200 pushes, 1 branch in 1 month
pytorchfinetuningdeep-learningmachine-learningtraining
santacml/pilim
Mar 2022 - Aug 2022
Contributions:66 commits, 68 pushes, 1 branch in 4 months
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