Senior HPC DevOps Engineer

EPAM is global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.

• 5+ years of experience in HPC or DevOps engineering roles
• Knowledge of MPI, OpenMP, and multi-node GPU communication protocols such as NCCL and GPUDirect
• Proven experience managing AWS GPU instance families including P-series, G-series, Tranium/Inferentia
• Hands-on mastery of AWS Capacity Blocks for ML, On-Demand Capacity Reservations (ODCRs), and Service Quota management
• Experience deploying containerized environments using Apptainer/Singularity, Docker, or Enroot
• Understanding of I/O performance bottlenecks with distributed file systems such as Lustre, GPFS, BeeGFS, or AWS FSx for Lustre
• Hands-on skill in profiling applications using NVIDIA Nsight or similar tools
• Experience deploying or scaling HPC workloads on cloud infrastructure using EFA, ParallelCluster, and parallel storage (FSx for Lustre)
• Proficiency in English at B2+ level

• Guide scientists and data teams in using the platform user interface for self-service workloads
• Advise users and manage infrastructure capacity balancing capacity blocks and on-demand usage
• Maintain automated pipelines for infrastructure provisioning and platform service deployments
• Resolve technical queries on job scheduling failures, cluster bottlenecks, and resource quotas
• Collaborate with developer experience teams to improve documentation
• Collaborate with engineering teams to monitor GPU utilization using tools such as CloudWatch or Prometheus
• Manage AWS GPU instance families and allocate compute for large-scale ML training and inference
• Ensure compute availability through capacity planning and reservation management
• Deploy containerized environments tuned for HPC and GPU pass-through
• Deploy and scale HPC workloads on cloud infrastructure using parallel storage and networking solutions

Benefits listed are available to employees only. Open to working with contractors with individually agreed B2B terms. Only selected candidates will be contacted.