ML Infrastructure Engineer

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• Keep real-time inference services healthy through alerting, live debugging, production incident resolution, rollbacks, and postmortems as part of a shared 24x7 on-call rotation
• Build and improve AWS infrastructure, including infrastructure as code, CI/CD pipelines, Kubernetes, Docker, autoscaling, monitoring, load testing, and cost control
• Maintain the GPU fleet through NVIDIA driver and CUDA upgrades, node provisioning and debugging, and capacity management
• Automate user access, including SSH credentials, service accounts, and developer environments for the science team
• Run real-time production data pipelines, including streaming ingestion into an online feature store and serving features to low-latency endpoints
• Orchestrate batch jobs with Airflow or Databricks Workflows
• Partner with applied scientists to productionize their prototypes and keep them healthy
• Write and review production Python, including validating AI-generated code

• At least 36 months of experience

• Opportunity to work abroad for up to two months per year
• Relocation opportunities within offices in 55+ countries
• Leadership development, career advising, soft skills, and well-being programs
• Certifications, including GCP, Azure, and AWS
• Unlimited access to EPAM's internal learning database
• Free English classes with certified teachers
• Discounts at local language schools, including online Kazakh courses
• Participation in the Employee Stock Purchase Plan
• Monetary bonuses for engaging in the referral program
• Medical and family care package
• Six trust days per year (sick leave without a medical certificate)
• Coverage of psychology sessions of your choice
• Benefits package including sports activities and discounts at stores and services
• Housing support program with preferential mortgage access through an Otbasy Bank partnership
• Enjoyable working environment, whether in the office or at home