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Nvidia GPU MLOps Solution Architect in United States

Do you want to be part of the team that brings new Artificial Intelligence (AI) technology to use in the field? We are looking for a DevOps savvy Solution Architect to join the NVIDIA Orchestration and Workflows team focused on Machine Learning, Deep Learning and Accelerated Data Analytics. If you are passionate about AI and how it can be applied to the real world, we should talk. NVIDIA is the world leader in GPU accelerated computing, and is looking for developers like you to design and build enterprise AI solutions using our newest technology. As an engineer on the Solution Architecture team, you will work closely with customers and partners to tackle hard problems in the industry and to help them deploy and operationalize AI solutions at scale. What you’ll be doing: * A huge part of the day-to-day job is developing repeatable pipelines for end-to-end Machine Learning and Deep Learning solutions. You will solve customer problems by building systems using the newest tools in virtualization, MLOps, ML engineering, DevOps, orchestration, Kubernetes, and AI Workflows. * Document and teach others what you know and have learned through delivering demos and developing POCs. This can vary from building hands-on training, to writing papers, developer blogs and instructing. * We make heavy use of conferencing tools, travel may be required for this role, as we work together with the customer to scope and deliver projects. * Above all, you will be the person that helps bring NVIDIA technology to life in the Enterprise. You are empowered and given all the tools to achieve this with the backing of all of NVIDIA, other Solution Architects and our Engineering teams. You’ll get to be the face and brains of NVIDIA that our customers will rely on. What we need to see: * 3 to 6 years of experience. * Strong foundational expertise, likely from a BS, MS or PhD degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or equivalent work experience. * Ideal candidates will have an established track record working with DevOps, virtualization and cluster management tools; including Docker/Containers, Kubernetes, Ansible. * Experience in Deep Learning and Machine Learning; experience with GPUs as well as expertise in using deep learning frameworks such as TensorFlow or PyTorch. * Understanding of dense datacenter design including compute, storage, and networking. Familiarity with Cloud and hybrid cloud architectures. * Strong analytical and problem-solving skills. * Ability to multitask efficiently in a dynamic environment. * Clear written and oral communications skills with the ability to effectively collaborate with executives and engineering teams. * Successful candidates will be able to demonstrate a strong desire to share knowledge with clients, partners and co-workers. Ways to stand out from the crowd: * Strong systems engineering, coding, and debugging skills. Including experience with Python, Ansible, Go, C/C++, Bash, and Linux. * Demonstrate expertise through projects or Open Source contributions in HPC, Data Analytics, Machine Learning, Deep Learning, Cloud Native Projects, Kubernetes, Slurm, or enabling GPU workloads. * Show a willingness and ability to dig into unfamiliar territories to tackle complex problems through examples in previous work. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression , sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. #deeplearning * Posted 30+ Days Ago * Full time * JR1934028

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