Nvidia Solutions Architect 

United States, Texas 

738961629

What You’ll Be Doing

• A considerable part of the day-to-day job is staying up on pioneering Deep Learning and Machine Learning ecosystems. You'll be called on to help architect and scale high-performance, distributed AI deployments on-prem or in the cloud that are built with the latest NVIDIA GPU supercomputers.

• Document what you know and teach others. This can vary from building targeted training for partners and other Solutions Architects to writing whitepapers, blogs, and wiki articles, to working through challenging problems with a partner on a whiteboard.

• Answer questions and provide mentorship. Work with Partner Business Managers to assist partners and customers on their critical projects. You will assist them in building AI-accelerated data centers by leveraging GPU and DPU capabilities, ensuring optimal returns on their investment.

• Lead and develop proof-of-concepts (PoCs) for solutions applied to enterprise and industrial applications such as LLM, RAG, recommender systems and image recognition using ML/DL frameworks.

• Support the business development team through the sales process for GPU/DPU/Network hardware/software products. Responsible for technical relationships and enabling customers in building innovative NVIDIA technology solutions.

• Partner with NVIDIA Engineering, Product, Sales teams to secure design wins at customers. Enable development and growth of NVIDIA product features through customer feedback and PoC evaluations.

What We Need To See

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields or equivalent experience.

• 5+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow, PyTorch and LangChain with GPU and CUDA experience being extremely advantageous.

• Experience working with DevOps on-prem or in cloud environments, including but not limited to Docker/Containers, Kubernetes, cloud APIs, IaaS and Data Center deployments,

• Deep understanding of dense data-center design including compute, storage, networking, cloud APIs and IaaS.

• Ability to multitask effectively in a dynamic environment.

• Strong analytical and problem-solving skills.

• Clear written and oral communication skills with the ability to effectively collaborate and coordinate across cross-functional teams in engineering, sales, marketing, product, and program management.

• Comfortable working in a customer-facing environment.

• Self-starter with a passion for growth, enthusiasm for continuous learning and sharing findings across teams.

Ways To Stand Out From The Crowd

• External customer-facing skill-set and background.

• Skilled in deploying ML/DL models at scale on cloud computing clusters in production.

• Development experience with NVIDIA software libraries and GPUs or DPUs.

• Knowledge of MLOps, DevOps and Cloud oriented workflows using Docker/containers, Kubernetes, cloud APIs, data center deployments etc.

• Knowledge of MLPerf, LLM, RAG, AWS, Azure or GCP.