Sviatoslav Skoblov
Machine Learning Engineer at Sociaro
Voronezh, Voronezh Oblast, Russia
Summary
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Rockstar🎓
Top SchoolSviatoslav Skoblov is a Machine Learning Engineer with 11 years of experience building production-ready ML and data solutions, currently driving ML efforts at Sociaro from Voronezh. He specializes in Python, NLP and deep learning, with a strong track record moving models into scalable deployments and improving hyperparameter optimization workflows. As an open-source contributor to the Amazon SageMaker Python SDK, he added GridSearch and Hyperband tuning strategies and expanded HPO flexibility—work that bridges research methods and cloud-native production needs. His background in applied mathematics and long tenure across consultancies and engineering teams give him both theoretical rigor and pragmatic delivery skills. Notably, he combines hands-on model development with engineering focus on reproducibility and efficient HPO at scale.
11 years of coding experience
7 years of employment as a software developer
Specialist, Applied mathematics and informatics, Specialist, Applied mathematics and informatics at Voronezh State University
Stackoverflow
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Github Skills (13)
hyperparameter-tuning10
machine-learning10
aws10
python10
sagemaker10
pytorch8
tensorflow8
scikit7
scikit-learn7
docker6
dockers6
kubernetes-pods5
kubernetes5
Programming languages (8)
Github contributions (5)
aws/sagemaker-python-sdk
Oct 2022 - Dec 2022
A library for training and deploying machine learning models on Amazon SageMaker
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 4 commits, 12 PRs in 1 month
Contributions summary:Sviatoslav's commits primarily focus on enhancing the hyperparameter tuning capabilities within the SageMaker Python SDK. They implemented support for the GridSearch and Hyperband strategies, which are key for optimizing machine learning model performance. Their contributions involved modifying the `tuner.py` and `session.py` files, adding new classes and configurations related to these tuning strategies, and improving the tests. They also added support for features like environment variables and flexible instance types within HPO jobs.
pytorchsagemakerdeployingmxnetpython
repushko/sagemaker-python-sdk
Dec 2023 - Mar 2024
A library for training and deploying machine learning models on Amazon SageMaker
Contributions:45 reviews, 2 PRs, 39 pushes in 2 months
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