Senior Solutions Architect, HPC and AI

Responsibilities

• Collaborate with NVIDIA’s training framework developers and product teams to drive adoption of the latest features.
• Assist customers and partners with the deployment, debugging, and efficiency optimization of AI workloads on extensive NVIDIA platforms.
• Benchmark new framework features, analyze performance, and provide actionable insights to internal and external stakeholders.
• Work directly with external customers to resolve cluster performance and stability issues and identify technical bottlenecks.
• Guide customers in scaling workloads efficiently and reliably on the latest generation of NVIDIA GPUs.
• Support Europe’s Sovereign AI initiative by helping customers implement advanced resiliency features within AI training pipelines.

Requirements

• BS, MS, PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or a related engineering field.
• 8+ years of experience in accelerated computing technologies at cluster scale.
• Strong programming skills in C, C++, or Python.
• Practical experience identifying and resolving bottlenecks in large-scale training workloads or parallel applications.
• Hands-on experience profiling and debugging large parallel applications.
• Solid understanding of CPU/GPU architectures, CUDA, parallel filesystems, and high-speed interconnects.
• Experience working with large compute clusters and resource management mechanisms such as SLURM or cloud-based clusters.
• Proficient knowledge of training pipelines and frameworks, including their internal operations and performance attributes.

Preferred Qualifications

• Experience debugging training pipelines running on thousands of GPUs in production environments.
• Hands-on experience with performance profiling tools like Nsight Systems and Nsight Compute.
• Deep understanding of NCCL, MPI, and low-level communication libraries.
• Ability to debug stability issues across the entire stack, including applications, frameworks, runtime libraries, and hardware.
• Understanding of LLM frameworks (PyTorch, Megatron-LM, NeMo) or inference tools (vLLM, TensorRT-LLM, SGLang).

About the Company

NVIDIA is the pioneer of accelerated computing. We are driving the era of AI, providing the infrastructure and software that power the world's most advanced computing workloads.