Overview
GPU Architect to design and architect multi-GPU scale-up/scale-out systems for next-generation AI datacenter platforms.
What you'll do
- Architect multi-GPU systems for scale-up and scale-out configurations.
- Define, modify, and evaluate future architectures for high-speed interconnects like NVLink and Ethernet.
- Architect RDMA-capable hardware and define transport layer optimizations for GPU-based large-scale AI workloads.
- Explore and build high-density multi-chiplet, multi-package, multi-node rack-scale AI systems with copper and optical interconnects between GPUs.
- Use system models to run simulations and perform bottleneck analyses for design trade-offs.
- Collaborate with GPU ASIC, compiler, library, and software teams for hardware-software co-design across compute, memory, and communication layers.
What you'll need
- BS/MS/PhD in Electrical Engineering, Computer Engineering, or equivalent area.
- 2+ years of relevant experience in system design and/or ASIC/SoC architecture for GPU, CPU, XPU, or networking products.
- Deep understanding of communication interconnect protocols including Ethernet, InfiniBand, NVLink, CXL, and PCIe.
- Proven ability to architect multi-GPU/multi-CPU topologies with awareness of bandwidth scaling, NUMA, memory models, coherency, and resilience.
- Strong analytical and system modeling skills for performance, power, and resilience.
- Excellent cross-functional collaboration and skills.
Nice to have
- Experience with NICs, DPUs, RDMA/RoCE, or InfiniBand transport offload architectures.
- Expertise in chiplet interconnect architectures or multi-node fabrics and protocols for high-performance distributed computing.
Details
- Location: India, Bengaluru.
- Hybrid work mode indicated by “#LI-Hybrid”.
Read the full description and apply on the company’s own careers page.
