Michael Kuchnik
Research Scientist at Meta
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolMichael Kuchnik is a Research Scientist specializing in systems for machine learning, with 11 years of experience designing high-performance ML data pipelines that prioritize both speed and developer ergonomics. His PhD work at Carnegie Mellon and subsequent roles at Meta and Google blend systems research, data representation, augmentation, and model validation into practical tooling—he contributed to Plumber, a tf.data profiling and diagnosis system. Comfortable running large-scale experiments across HPC and cloud environments, he has applied ML to storage, logs, and ETL workloads and brought systems-thinking to model training bottlenecks. Based in Boston, he combines deep academic rigor with hands-on production experience, often surfacing tuning opportunities that are easy to miss during typical ML development.
11 years of coding experience
10 years of employment as a software developer
Bachelor's Degree Computer Engineering, Bachelor's Degree Computer Engineering at Georgia Institute of TechnologyDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Carnegie Mellon University
Stackoverflow
11reputation
175reached
0answers
1question
Github Skills (57)
python10
machine-learning10
ml10
datasets10
schema-org10
deep-learning10
tensorflow10
deep-neural-networks10
neural-network10
json-ld10
numpy9
gpu9
hpc-applications9
jax8
tensorflow-io8
Programming languages (6)
Github contributions (5)
mkuchnik/PlumberApp
Feb 2022 - Mar 2022
Repository to go along with the paper "Plumber: Diagnosing and Removing Performance Bottlenecks in Machine Learning Data Pipelines"
Contributions:3 releases, 57 commits, 48 pushes in 1 month
data-pipelinedata-pipelinesgomachine-learning
mkuchnik/CephEvolution
Aug 2019 - Dec 2019
Contributions:74 commits, 73 pushes, 2 branches in 4 months
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