Solutions Architect - CPU and LPU

Job description

aNVIDIA’s Solutions Architect team is looking for a software-focused Solutions Architect to drive adoption of next-generation AI infrastructure across NVIDIA CPU platforms and LPU-based inference systems. This role will focus on NVIDIA CPUs, including Grace, Vera, and future CPU generations, and on LPU platforms and LPX-class systems used to accelerate large language model inference and other latency-sensitive generative AI workloads. We are looking for someone who understands that AI efficiency is a full-stack challenge spanning model architecture, runtime, compiler, serving framework, host software, memory movement, and workload partitioning across CPU, GPU, and LPU.

As a Solutions Architect, you will be the first line of technical expertise between NVIDIA and our customers for CPU- and LPU-centric AI system design. You will help customers understand how NVIDIA CPUs and LPU-based systems can improve the efficiency, latency, throughput, and total cost of their AI workloads, especially when deployed alongside NVIDIA GPUs in heterogeneous production environments. Your work will range from proof-of-concept development and software stack optimization to technical leadership with customer architects, engineering teams, and senior decision makers. You will engage directly with developers, ML engineers, researchers, platform architects, and IT leaders to identify bottlenecks, design optimization strategies, and build deployable reference architectures. You will also work closely with NVIDIA engineering, product, and field teams to translate customer needs into platform feedback, solution patterns, and roadmap inputs.