ML Infrastructure Operations Engineer

Description: Configure and maintain ML environments using Kubernetes, Docker, and YAML-based configurations. Execute, monitor, and validate distributed ML training workloads across multi-node accelerator clusters. Review, modify, and execute Python and Bash scripts to automate workload execution and adjust runtime configurations. Troubleshoot workload failures, collect logs, identify infrastructure or configuration issues, and document findings. Track workload execution status, communicate test progress, and collaborate with engineering teams to improve reliability and operational efficiency. Requirements: 3+ years of experience in ML Operations, Software Testing, Systems QA, Linux Systems Administration, or a related technical role. Strong proficiency with Linux command-line operations and shell environments. Experience reading and modifying Python and Bash scripts. Familiarity with Kubernetes, Docker, and containerized environments. Experience executing and monitoring distributed workloads. English proficiency at C1 level. Benefits: Base salary. Major Medical Expenses Insurance (includes dental and vision plan). 15 days of Christmas bonus. 25% vacation bonus. 12 vacation days (starting from the first year). Social security. Biweekly grocery vouchers.