devops engineer for AI/ML workloads

EPAM develops enterprise software products, open source solutions, and accelerators.

• Develop and maintain infrastructure for data pipelines;
• Build and improve CI/CD for data processes and infrastructure;
• Automate deployments through Infrastructure as Code;
• Set up pipeline orchestration, monitoring, and alerting;
• Diagnose and resolve incidents, improving stability and performance;
• Participate in code review and mentor junior/middle engineers;
• Collaborate with data engineers and analysts to optimize data workflows.

• 3+ Years of experience in DevOps or Data Engineering;
• Experience supporting AI/ML workloads and building or maintaining ML infrastructure (MLOps);
• Hands-on experience with one cloud platform: AWS, GCP, or Azure;
• Proficiency in Docker, Kubernetes, and Terraform or equivalent IaC;
• Expertise in pipeline orchestration tools such as Airflow, Dagster, or Prefect;
• Familiarity with data lake/DWH concepts and big data processing, including Spark, Kafka, or equivalent;
• Strong programming skills in Python, SQL, and Bash;
• Competency in CI/CD setup with GitLab CI, GitHub Actions, or Jenkins;
• Autonomy and ownership of outcomes;
• Willingness to share knowledge and mentor;
• Attention to detail, reliability, and quality;
• English proficiency at an Upper-Intermediate level (B2) or higher;
• Nice to have: Knowledge of monitoring and observability tools such as Prometheus, Grafana, and ELK, exposure to LLM/GenAI tooling, understanding of data security and data quality practices.

• Location-specific conditions and benefits are available.