Nvidia Deep Learning Solution Architect 

China, Beijing, Beijing 

76182212

NVIDIA is looking for a Solutions Architect or Data Scientist to work with our largest global alliance partners to enable them with our portfolio of GPU Accelerated Computing solutions i.e. Machine Learning and Deep Learning, specifically Generative AI and to build comprehensive multi-cloud, hybrid and on-prem solutions.

be doing:

• Creating or running Proof of Concept and Demos that require presentation skills, explanation of complex topics, writing Python code to execute data pipelines and train ML/DL models and deploy on container based orchestrators.

• A considerable part of the day-to-day job is keeping up to date on the state of the art in the production Deep Learning and Machine Learning ecosystem. You'll be called on to help architect and scale high-performance, distributed AI deployments that are built on the latest NVIDIA GPU supercomputers.

• Document what you know, and guide others. This can vary from building targeted training for partners and other Solutions Architects to writing whitepapers, blogs, and wiki articles, to work 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 mission-critical projects. You will help them build their GPU enabled Accelerated Compute datacenters and get the most out of their investment.

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

What we need to see:

• BS or MS in Engineering, Mathematics, Physics, or Computer Science (or equivalent experience).

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

• Experience working with DevOps, including but not limited to Docker/Containers, Kubernetes, and Data Center deployments.

• Deep understanding of dense datacenter design including compute, storage, and networking.

• 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 with management and engineering.

• Have a strong desire to share knowledge with clients, partners and co-workers.

Ways to stand out from the crowd:

• Extensive knowledge and hands-on experience with recent advancements in LLMs and GenAI.

• Experience developing with ML/DL frameworks and MLOps ecosystem of partners and solutions in the cloud and on-prem

• Background with cloud based solution designing, APIs and Microservices, orchestration platforms, storage solutions and data migration techniques

• Experience or good knowledge of server architectures, PCIe topologies, Infinibadand and other networking technologies and Operating systems

• Have a willingness and ability to dig into unfamiliar territories to tackle complex problems and be a great listener.