NVIDIA is seeking a Senior Solutions Architect for its Higher Education and Research Team to support university researchers in advancing foundation models and multimodal AI. This role involves collaborating with academic developers on various AI systems, including LLMs and VLMs, while providing guidance on GPU-accelerated training and inference studies. The architect will help build research prototypes and analyze system performance across different computing environments. The position requires strong technical expertise and the ability to translate lab feedback into actionable insights.

• BS, MS or PhD in Computer Science, AI/ML, Electrical Engineering, Applied Mathematics, or a related technical field, or equivalent experience.
• 8+ years of hands-on experience with AI systems, accelerated computing, distributed training, inference studies, or research-scale generative AI workflows.
• Deep foundational AI expertise across LLMs, VLMs, multimodal models, reasoning, long-context models, fine-tuning, post-training, agentic AI, and evaluation.
• Strong systems fluency in PyTorch or JAX, Python, Linux, distributed AI, data loading, checkpointing, memory optimization, batching, scheduling, latency, and throughput.
• Experience guiding faculty, graduate researchers, and research-computing teams on benchmarks, reproducibility, reliability, safety, agent evaluation, and research impact.
• Clear communication, technical judgment, and comfort turning complex model, agent, and infrastructure questions into practical next steps for labs.

• Partner with universities to shape high-impact work on foundation models, generative AI, multimodal AI, reasoning systems, AI agents, and AI systems.
• Advise labs on GPU-accelerated training, inference studies, agent evaluation, tool-use methods, data pipelines, scaling experiments, and reproducible workflows.
• Help build research prototypes with researchers utilizing the NVIDIA full stack.
• Analyze throughput, memory, parallelism, latency, and scaling across workstations, multi-GPU servers, and campus HPC clusters.
• Translate lab feedback into technical examples, workshops, roadmap input, and adoption guidance for NVIDIA teams.
• Travel up to 20%.

• Employees at NVIDIA are often offered comprehensive, day-one benefits—including medical, dental, and vision coverage with HSA support, life and disability insurance, an Employee Assistance Program, and a 401(k) with auto-enrollment. Many roles also have generous time off and holidays, donation matching (up to $10,000), and a wide menu of extras like FSAs, commuter benefits, legal and identity-theft protection, pet insurance, and wellness discounts. Optional programs can include student-loan and home-purchase support, plus family care resources and expert medical services.