Principal Software Engineer Scale Up Networking GPU Centric
Principal Software Engineer Scale-Up Networking (GPU-Centric) This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from an HPE office. Key Responsibilities Architect Deliver Scale-Up Networking Required Skills Experience Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Security-First Mindset, Solutions Design, Testing Automation, User Experience (UX) #india #highperformancecompute
High Performance Computing, AI and Labs is a critical element of HPE. We are focused on delivering innovative solutions that accelerate our customers digital transformation, enabling them to tackle their complex, and data-intensive workloads. Combining deep expertise and the development of the world s most cutting-edge, high-performance supercomputers, is defining the next era of computing delivering valuable insight innovation. Join us and redefine what s next for you.
What youll do:
- Design and implement GPU-aware networking paths for high-bandwidth, low-latency intra-node communication.
- Develop and optimize GPU NIC GPU data movement, shared memory models, and DMA pathways.
- Work with NVIDIA CUDA, NVLink, NCCL , and AMD ROCm, InfinityFabric, RCCL teams to integrate and optimize scale-up communication semantics.
- Drive improvements to DMA engines, BAR mappings, ATS/IOMMU , and GPU memory registration workflows.
- Enhance and extend Libfabric, UCX, CXI, SHMEMX, OpenMPI for GPU-accelerated scale-up workflows.
- Optimize communication collectives, transport layers, and GPU-direct capabilities.
- Characterize and tune multi-NIC per socket , NUMA-zone mapping, GPU locality, CQ/queue design, and CPU/GPU topology optimization.
- Lead upstream contributions to open-source projects (OFI, UCX, OpenMPI, RCCL/NCCL enablement).
- Partner with HPC/AI ecosystem teams to shape future architectures.
- Own complex debugging across driver, runtime, GPU, kernel, and user-space boundaries.
- Develop profiling workflows using Nsight, ROCm tools, eBPF, perf, etc.
- 10 15+ years building high-performance networking, GPU, or kernel-level software .
- Deep expertise in C/C++ , Linux internals, memory management, RDMA, PCIe, IOMMU, ATS, DMA engines.
- Strong understanding of CUDA, ROCm, GPU memory models, P2P, GDS (GPUDirect Storage), GDR (GPUDirect RDMA) .
- Hands-on experience with MPI, SHMEM, Libfabric, UCX , or similar communication stacks.
- Proven experience driving architecture , cross-org technical decisions, and upstream contributions.
- Ability to mentor senior engineers, influence multi-team designs, and own end-to-end delivery.
- Experience with NIC architecture (CXI, RoCE, Infiniband, Slingshot, NVLink Switch).
- Experience optimizing collectives (AllReduce/AllGather) on GPUs.
- Background contributing to open-source HPC/AI libraries .
- Familiarity with HPC system architecture , NUMA tuning, and multi-accelerator systems.
Additional Skills:
Job:
Engineering Job Level:
TCP_05 HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity .
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