Senior Solutions Architect - AI @ NVIDIA

Are you a computational scientist, engineer, or data scientist passionate about working on the frontiers of artificial intelligence (AI) and high-performance computing (HPC)? NVIDIA is searching for a Solutions Architect to join our team in Canada and help customers solve challenging problems using AI. Solutions Architects are the primary technical contacts for our customers and engage deeply with scientific researchers and application developers. We need individuals who can develop positive relationships with researchers and developers, learn their requirements and work to bring solutions that enable their success. Your primary responsibilities will be to foster machine learning technical engagements with our largest Canadian enterprise customers.What you’ll be doing:You will be part of Canadian Solutions Architect team engaging with AI developers and engineers to develop a keen understanding of their goals, strategies, and technical needs, and drive NVIDIA technology adoption in data center, edge, and cloud deployments.Facilitate AI use cases and proof-of-concepts on the NVIDIA platform.Collaborating with other solution architects, engineering and product teams, understanding their technical needs and helping define high-value solutions.Strategically supporting and partnering with Canadian customers and industry-specific solution partners to help them adopt and build solutions using NVIDIA technology.What we need to see:MS or PhD in Computer Science, Engineering, or related field from an accredited university.5+ years of experience.Experience with modern AI software tools including PyTorch, JAX, TRT-LLM, vLLM, SGLang, or other frameworks.Programming experience with data science languages like Python, and/or HPC languages such as C/C++/Fortran.Experience with GPUs and accelerated computing.Ways to stand out from the crowd:Excellent knowledge of theory and practice of deep learning, reinforcement learning, and/or large language models.CUDA/GPU optimization or CUDA-X library experience.Knowledge of MLOps technologies such as Docker/containers, Kubernetes, as well as cloud and data center deployments.Experience deploying large-scale GPU clusters.Experience deploying AI inference at scale on-premise or in the cloud.We are an equal…

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