MLOps/Ai Engineer

Hamkorbank • Russian: C1 • Python • 6 days ago
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Location
In office (Tashkent)
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Hamkorbank

Hamkorbank is a prominent commercial financial institution headquartered in Andijan, Uzbekistan, and was established in 1991. The bank provides a comprehensive range of services including retail and corporate lending, mortgage financing, payment cards, and various deposit products in both national and foreign currencies. It operates through an extensive network of more than 200 service offices across the country, serving over three million active clients with the support of international shareholders such as the IFC and FMO.
hamkorbank.uz • HQ: Andijan, Uzbekistan • Credit Cards • Lending • Financial Services • 11-50 employees • Est. 1991

Обязанности:

  • Настройка и автоматизация CI/CD (GitLab CI, Jenkins, ArgoCD).
  • Управление инфраструктурой (Kubernetes, Helm, Terraform, Ansible, GitOps).
  • Контейнеризация и сопровождение AI/ML сервисов (GPU/CPU).
  • Настройка мониторинга и логирования (Prometheus, Grafana, EFK), мониторинг AI/ML.
  • Обеспечение отказоустойчивости, автоскейлинга, резервного копирования и безопасности (RBAC, Secrets, Vulnerability Scan).
  • Внедрение и сопровождение MLOps: RAG, deployment и serving LLM, ML lifecycle.
  • Автоматизация процессов, разработка скриптов и технической документации.
  • Взаимодействие с Dev/ML командами, участие в on-call, устранении инцидентов и postmortem.
Требования:
  • Опыт с CI/CD (GitLab CI, Jenkins, ArgoCD).
  • Уверенное знание Kubernetes, Helm, Terraform, Ansible, GitOps.
  • Опыт работы с Prometheus, Grafana, EFK.
  • Практический опыт в MLOps, RAG, deployment/serving LLM и ML lifecycle.
  • Навыки автоматизации на Bash, Python или Go.
  • Опыт сопровождения AI/ML инфраструктуры, участия в on-call и ведения технической документации.
Условия:
  • Работу над современным AI-продуктом с использованием LLM и RAG.
  • Возможность влиять на архитектуру и развитие AI-инфраструктуры.
  • Работу с высокопроизводительными GPU-кластерами и современным серверным оборудованием.
  • Развертывание и оптимизацию крупных AI/ML-моделей на мощных видеокартах.
  • Конкурентную заработную плату, возможности обучения и профессионального роста.
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