Principal HPC Network Engineer

We are seeking a Principal HPC Network Engineer to support advanced AI, research, and Kubernetes-based GPU infrastructure for a major global technology client.

An ideal candidate is an ownership-driven, hands-on network expert who combines deep low-level troubleshooting with architectural thinking and clear communication in complex AI/HPC, Kubernetes, and GPU infrastructure environments.

Feel free to work remotely from anywhere across Lithuania or connect with colleagues at our Vilnius and Kaunas offices.

Responsibilities

• Architect, operate and troubleshoot high-performance InfiniBand/RDMA and Ethernet fabrics for large-scale GPU clusters and distributed AI/LLM workloads
• Design and evaluate cluster network topologies, including Fat-tree, Clos, Rail-optimized and Dragonfly, based on workload scale and performance needs
• Optimization of host-side networking, including NIC configuration, drivers, firmware, IRQ affinity, NUMA placement, PCIe topology and GPU-to-NIC communication paths
• Tune and troubleshoot RDMA/RoCE, NCCL/MSCCL and collective communication performance for multi-node GPU training workloads
• Design and maintain Kubernetes networking for GPU clusters, including CNI plugins, network policies, multi-NIC pods, RDMA/GPU device plugins and workload orchestration integration
• Support for SmartNIC/DPU technologies such as NVIDIA BlueField where applicable, including SR-IOV, offload, isolation and security use cases
• Build and improve network observability, including metrics, dashboards, alerts, congestion detection, latency tracing, SLO reporting and capacity/performance analysis
• Collaboration with Kubernetes, storage, GPU infrastructure, observability and AI research teams to resolve network and I/O bottlenecks and improve workload reliability

Requirements

• 8+ years of experience in network, infrastructure, HPC, SRE or similar engineering roles, with 4+ years focused on HPC, AI/ML or GPU cluster networking
• Expert-level experience in high-performance networking for HPC, AI/ML, GPU clusters or large-scale compute environments
• Knowledge of InfiniBand fabrics, including NDR/HDR or comparable high-speed generations, subnet managers, fabric configuration, topology and troubleshooting
• Understanding of RDMA networking concepts, including InfiniBand, RoCE/RoCEv2, GPUDirect-related patterns, congestion behavior and performance tuning
• Skills in Kubernetes and container networking for GPU or distributed workloads, including CNI concepts, network policies, multi-NIC patterns and RDMA/GPU device integration
• Proficiency in Linux networking and host-side troubleshooting, including NIC configuration, drivers, firmware, IRQ affinity, NUMA awareness, PCIe topology, MTU, offloads and performance diagnostics
• Expertise in network observability and performance management, including telemetry, traffic monitoring, congestion detection, latency analysis, SLOs, capacity planning, alerting and troubleshooting across L1-L4, fabric and RDMA layers
• Practical knowledge of distributed AI training communication patterns, including NCCL-based workloads and collective operations such as all-reduce and all-gather
• Familiarity with host-side networking, including NICs, PCIe topology, NUMA awareness and GPU-to-NIC affinity
• Capability to perform troubleshooting, root-cause analysis, documentation and communication with client engineering teams, researchers and platform stakeholders

Nice to have

• Knowledge of Azure Networking, Ethernet and GPGPU/GPU
• Skills in Grafana, Prometheus and Network Administration
• Proficiency in Python and UNIX shell scripting
• Capability to perform Infrastructure as Code development and maintenance

We offer

• Engineering Heritage: Best-in-class experts sharing a culture of engineering excellence and tackling complex engineering challenges for over 30 years
• Advanced Tech Stack: Innovative projects where you can apply or enhance your expertise in Cloud, Data, AI, and other emerging technologies
• World-Class Clients: Work closely with 340+ of the Forbes Global 2000 on creating disruptive solutions that make a global impact
• Professional Growth: Exceptional support for career development with comprehensive resources for upskilling or reskilling in pioneering practices
• GenAI Community: Strong AI competencies with 600+ experts across 55+ locations driving GenAI-enabled transformation journeys
• Entrepreneurial Culture: If you're passionate and dedicated to improving business transformation, we provide the support you need to bring your ideas to life
• Hybrid Setup: The flexibility to work from any location in Lithuania, whether it's your home or our dynamic offices in Vilnius and Kaunas
• Other Benefits: Additional vacation and trust days, private health insurance, Employee Stock Purchase Plan and more

Salary range €5.6K-€7.2K gross, based on your experience and interview results.

EPAM is a leading global provider of digital platform engineering and development services. For over 30 years, our team has helped leading brands navigate the waves of digital transformation, building solutions that help them stay competitive through constant market disruption.With offices in 55+ countries, EPAM has grown in Lithuania to over 1,300+ talented innovators in just 5 years. We foster creativity and unconventional ways of doing things, welcoming like-minded professionals to join us.