Dimitri Kalugin
Quantitative Researcher
Paris, Ile-de-France
Summary
👤
Senior🎓
Top SchoolDimitri Kalugin is a quantitative researcher and machine learning engineer with nine years of experience building production ML systems, most recently transitioning from voice biometrics and ASR work at SoundHound to quantitative research at Morgan Stanley. Trained at École Polytechnique, MIPT and Yandex School of Data Analysis, he blends rigorous academic foundations with hands-on engineering across startups and large firms including Facebook and MWM. His background spans signal-processing-driven voice authentication, large-scale speech models, and data-driven trading research, reflecting a rare cross-domain fluency between audio ML and finance. Based in Paris, he is comfortable taking research prototypes to production and navigating the constraints of latency, privacy, and operational robustness in real-world systems.
9 years of coding experience
4 years of employment as a software developer
Ingénieur, Ingénieur at École PolytechniqueMaster of Science - MS Computer Science, Master of Science - MS Computer Science at Moscow Institute of Physics and Technology (State University) (MIPT)Graduate Data Science, Graduate Data Science at Yandex School of Data Analysis
English, Russian, Ukrainian, French
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (16)
multimodal6
python6
deep-learning5
machine-learning5
pytorch4
aws-lambda4
generative-ai4
mlops3
kubernetes3
llm3
data-science3
tensorflow3
llm-inference2
bentoml2
model-management2
Programming languages (2)
Github contributions (5)
KaluginD/MIPT-4-term
Apr 2017 - Dec 2017
Contributions:12 commits, 11 pushes, 1 branch in 8 months
KaluginD/MIPT-1-2-terms
Apr 2017 - Dec 2017
Contributions:23 pushes, 1 branch in 8 months
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