Summary
Anton Alekseev is a Senior MLOps SRE with nine years of experience building and running cloud-native infrastructure and ML platforms across industry and academia. He has designed and operated production ML tooling—Kubernetes, Seldon/KServe, ClearML, Triton—and optimized GPU sharing and container runtimes for efficient model workloads. At Avito and Selectel he led MLOps platform work and before that delivered end-to-end DevOps and IIoT solutions for Gazprom Neft, combining Python backend, Terraform/Ansible automation, and OpenStack/Proxmox administration. He also teaches masters-level courses and leads curriculum development for Yandex Practicum, bringing practical lab infrastructure to students and managing authors and cloud cost optimization. Anton holds advanced degrees in cyber-physical systems and is completing PhD work, a background that informs his focus on reproducible, auditable ML pipelines and industrial control integrations. Colleagues know him for pragmatic automation that bridges research prototypes to reliable production systems.
9 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Peter the Great St.Petersburg Polytechnic University
English, French, Russian