Solutions Architect for NVIDIA's CPU platforms and LPU systems focusing on next-gen AI workloads. Collaborate with customers to enhance AI efficiency and optimize generative AI solutions through architecture and design optimization.
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.
Requirements
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.
Benefits
NVIDIA is committed to fostering a diverse work environment and prides itself on being an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate on any characteristic protected by law.
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