Gustavo Malkomes
Sr. Scientist II at Lila Sciences
Cambridge, Massachusetts, United States
Summary
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Senior🎓
Top SchoolGustavo Malkomes is a senior scientist and ML engineer with a decade of experience specializing in sequential decision-making under uncertainty, including Bayesian optimization, AutoML, and active learning. He has bridged top-tier research (ICML, NeurIPS) with production systems, advancing multi-objective and active learning methods at SigOpt and then scaling LLM performance on Intel AI accelerators after the acquisition. Gustavo contributed to open-source performance tooling such as Hugging Face Optimum Habana and vLLM, helping deploy large models more efficiently on specialized hardware. Based in Cambridge, MA, he combines a PhD in computer science with hands-on platform-building for enterprise ML workflows, and is known for translating principled research into practical, high-impact engineering.
10 years of coding experience
Master's degree, Computer Science, Master's degree, Computer Science at Universidade Federal do CearáDoctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at Washington University in St. Louis
English, Portuguese
Github Skills (9)
bayesian9
regression8
active-learning7
matlab7
statistics7
python6
gaussian-processes3
pytorch2
algorithms1
Programming languages (3)
Github contributions (5)
gustavomalkomes/abo
Oct 2018 - Mar 2021
Contributions:4 commits, 3 pushes, 1 branch in 2 years 4 months
gustavomalkomes/active_gp_learning
Jan 2019 - May 2019
This package provides a set of tools for performing active-learning with Gaussian Processes.
Contributions:9 commits, 2 PRs, 16 pushes in 3 months
gaussian-processes
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