Solutions Architect - CPU and LPU

Responsibilities

• Evangelize NVIDIA CPU platforms, including Grace, Vera, and future generations, as well as LPU-based systems and LPX-class platforms, with a strong focus on AI software stacks and workload efficiency.
• Help customers design and optimize AI workloads across CPU, GPU, and LPU, improving latency, throughput, utilization, and overall cost efficiency.
• Analyze and tune LLM and generative AI pipelines across serving, runtime, memory, I/O, batching, scheduling, and orchestration layers.
• Build proof-of-concepts, reference architectures, and technical guidance in partnership with Engineering, Product, and Sales teams.
• Establish trusted technical relationships with customer architects, infrastructure teams, and senior leaders, becoming a strategic advisor for heterogeneous AI system design.
• What we need to see
• MS or PhD in Computer Science, Engineering, Mathematics, Physics, or a related field, or equivalent experience, plus 5+ years in AI systems, infrastructure, performance engineering, or solution architecture.
• Strong understanding of modern CPU architecture, Linux systems, and software performance tuning, along with hands-on experience in AI inference for LLM, generative AI, or agentic AI workloads.
• Experience optimizing heterogeneous systems involving CPU and accelerators, with familiarity in frameworks such as PyTorch, Triton, TensorRT-LLM, vLLM, or ONNX Runtime.
• Strong programming, problem-solving, and communication skills, with the ability to work effectively with both technical teams and senior customer stakeholders.

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