We are hiring a Senior ML/Data Ops Engineer to join our Data Platform department, which is focused on solving tasks in machine learning and data engineering. We aim to improve our architectural and infrastructural solutions, so we absolutely need someone who can deploy the best solutions in minimal time.
What you'll be doing
Develop and maintain GitLab CI/CD pipelines;
Deploy and maintain development and production environments for ML Engineers and Data Engineers;
Deploy and maintain MLOps tools for fast delivery and updating ML models;
Deploy and maintain specific data engineering storages and tools such as Clickhouse, Redis, Airflow, Kafka, PySpark, Debezium, etc;
Implementation, governance and support of access policies to the above-mentioned resources and tools.
Skills, Knowledge and Expertise
5+ years of experience as an MLOps, DevOps, Infrastructure Engineer;
Proficiency in cloud computing services;
Experience with CI/CD tools and practices;
Familiarity with containerization and orchestration technologies (e.g Docker, Kubernetes);
Strong knowledge of automation and scripting languages (e.g Python, Bash);
Experience with infrastructure as code (e.g Terraform).
Experience on Google Cloud Platform;
Experience working as an ML Engineer, Data Engineer or Architect
