Leonardo Apolonio
Staff Machine Learning Engineer at Qualtrics
Washington, District of Columbia, United States
Summary
👤
Senior🎓
Top SchoolLeonardo Apolonio is a Staff Machine Learning Engineer with 11 years of experience building production-grade NLP and ML systems that make AI operational, especially for conversational customer experience. He has led applied research and platform work at Qualtrics, Oracle Data Cloud, and DARPA, shipping scalable pipelines and model deployments that process billions of events and web pages. Comfortable across the ML lifecycle, he pairs deep NLP expertise (NER, topic classification, text CNNs) with hands-on infrastructure skills in big data, CI/CD, and Spark to close the verification bottleneck for AI at scale. He also teaches and mentors—bridging academic rigor from Georgia Tech and Maryland with practical engineering as a boot-camp instructor and cross-functional leader. An interesting detail: he’s tackled both adversarial research (anomaly and hate-speech detection) and high-throughput product classification, showing a rare mix of investigative research and production engineering.
11 years of coding experience
9 years of employment as a software developer
B.S., Computer Engineering, B.S., Computer Engineering at University of Maryland - A. James Clark School of EngineeringMS in Computer Science, Computer Science, Master, MS in Computer Science, Computer Science, Master at Georgia Institute of TechnologyHigh School Diploma, High School Diploma at Baltimore Polytechnic Institute
English
Stackoverflow
1,117reputation
92kreached
8answers
21questions
Github Skills (191)
transformers10
language-model10
python10
snorkel10
flax10
datasets10
deep-learning10
nvidia-docker10
machine-translation10
in-progress10
training-data10
autoencoder10
neural-network10
transformer10
nlp10
Programming languages (11)
Github contributions (5)
lapolonio/machine-learning-for-nlp-guide
Mar 2019 - Aug 2020
Contributions:34 commits, 33 pushes, 1 branch in 1 year 4 months
lapolonio/text_classification_tutorial
Sep 2019 - Dec 2019
Enterprise Solution for Text Classification (using BERT)
Contributions:35 commits, 18 pushes, 1 branch in 3 months
nlpclassificationberttext-classificationnatural-language-processing
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