Senior Solutions Architect, Gen AI Manufacturing

We are looking for a Senior Solutions Architect, GenAI Manufacturing to engage with customers, partners, and other NVIDIA software engineers to support applications and platforms that leverage NVIDIA technology that will be adopted across all industry segments. At NVIDIA, our Solutions Architects are drawn from elite developers and scientists who enjoy working with the latest in GPU and Networking hardware and software! NVIDIA’s platforms for machine learning, deep learning and high-performance computing have already made a major impact and are broadly used across leading North America companies. Our success has been based on vertical focus industry business development, building a strong developer ecosystem, and scaling out the business using a broad partner channel including HW OEMs, Cloud Service Providers, Global System Integrators, and VARs. 

We need a passionate, hardworking, and creative individual to help us pursue more of these opportunities in Manufacturing niche areas coupled with HPC, NLP, Reinforcement Learning, Machine Learning, and Deep Learning (AI)! This role requires becoming a trusted technical advisor and leader to our partners and customers who believe that deep learning, data science, and artificial intelligence is a new computing revolution and has the potential to transform industries. A Solutions Architect is the bridge of technical expertise between our industry teams, our partners and our customers. Dynamically engaging with internal developers, scientific researchers, data scientists, IT managers, and senior leaders is an important part of the Solutions Architect role, and will give you experience with a range of partners and concerns. 

What you'll be doing: 

• Partner with our industry and account teams to develop a keen understanding of customer goals, strategies, and technical needs as well as help to define and deliver high-value solutions meeting these needs. 

• Document what you know and teach others. This can vary from building targeted samples, to writing whitepapers, blogs, and wiki articles, to simply working through hard problems with a customer on a whiteboard. 

• Be an industry leader with vision on integrating NVIDIA technology into Manufacturing use cases with AI, HPC, and enterprise GPU and networking architectures for advanced applications both in the datacenter and at the edge. 

• Strategically partner with lighthouse customers and industry-specific solution partners targeting our computing platform. 

• We make heavy use of conferencing tools, but some travel is required for this role. Be empowered to find the best way to get your job done and do what it takes to make our partners and customers successful. 

What we need to see: 

• MS or PhD in Engineering, Mathematics, Physics, Computer Science or equivalent experience. 

• 8+ years of work-related experience in manufacturing domains - e.g. humanoids, robotics, manufacturing, data science or software development with knowledge of parallel computing with GPUs. 

• Background working with modern application deployment practices including but not limited to Docker/Containers and Kubernetes. 

• Experience with modern Deep Learning software architecture and frameworks. 

• Strong written and oral communication skills with the ability to effectively collaborate with management and engineering. 

• Experience supporting customers/partners in technical engagements. 

• Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects. 

• Expert analytical and problem-solving skills. 

Ways to stand out from the crowd: 

• Experience applying GenAI to manufacturing, robotics, aerospace use cases; frameworks like Tensorflow, Pytorch, TRT, and models like Vision Transformer; LLM for code generation and verification. 

• Experience applying optimization to networking - RDMA, RoCE, GPUDirect. Network tuning and RAPIDS query optimization. 

• Experience using GPU programming and design practices. 

• CUDA programming and optimization experience. 

• Artificial Intelligence: Deep Neural Network research and development experience with specialized domains; Machine Learning research and development experience with industry data; published record of thought leadership in a technical area of the manufacturing industry segment.