Aleksandr Seliverstov
Head Of MLOps at X5 Tech
Krasnodar Krai, Russia
Summary
🤩
Rockstar🎓
Top SchoolAleksandr Seliverstov is a seasoned software and ML engineering leader with 11 years of hands-on development and over five years managing multidisciplinary teams, currently shaping MLOps practice across 10+ product teams and 50+ engineers at X5 Retail Group. He built scalable engineering processes — hiring pipelines, mentoring programs, CI/CD templates and Kubernetes deployments — that cut project launch times from weeks to hours and dramatically reduced technical debt. Earlier, he led development of the open-source DeepPavlov NLP library, contributing backend improvements that strengthened model training, dataset handling and Telegram integrations. Known for turning research prototypes into reproducible production systems, he also delivered state-of-the-art Russian NLP models and transformed slow release cadences into biweekly deliveries. Based in Krasnodar Krai, he blends deep technical curiosity with pragmatic leadership to scale teams and operationalize ML in retail.
11 years of coding experience
20 years of employment as a software developer
Specialist Mathematician - System Engineer, Specialist Mathematician - System Engineer at Kuban State University (KubSU)
Английский, Русский
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (6)
machine-learning10
nlp10
tensorflow10
python10
deep-learning9
data-handling9
Programming languages (3)
Github contributions (5)
deeppavlov/DeepPavlov
Jan 2018 - Mar 2019
An open source library for deep learning end-to-end dialog systems and chatbots.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:18 releases, 181 commits, 402 PRs in 1 year 2 months
Contributions summary:Aleksandr's commits primarily involve modifications to the `deeppavlov` repository's core functionality, specifically related to the integration of the `telegram_utils` module and the modification of the SQuAD model and the handling of datasets. The user made changes to the `telegram_utils` module. Furthermore, the user improved the data handling within the datasets, as well as modifications to the LRScheduledTFModel, thereby indicating a focus on improving model training and usage. These changes suggest a focus on back-end development.
dialog-systemsdialogue-managerbotintent-classificationdialogue-systems
deeppavlov/sbrf_bot
Jul 2018 - Aug 2018
Contributions:12 commits, 2 PRs, 10 pushes in 10 days
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