Solutions Architect - Cloud AI

We are excited to announce an opening for a Cloud Solution Architect at NVIDIA and are seeking a passionate individual with a strong interest in AI and machine learning! If you are enthusiastic about contributing to projects that push the boundaries of what is possible with cloud scale AI, we invite you to read on. NVIDIA is renowned as one of the most sought-after employers in the technology world, offering highly competitive benefits. We are home to some of the most innovative and forward-thinking individuals globally. If you are creative, autonomous, and eager to apply your skills and knowledge in a dynamic environment, we want to hear from you!

What you'll be doing:

• Working as a key member of our cloud solutions team, you will be the go-to technical expert on NVIDIA's products, helping our clients build state-of-the-art IT infrastructures.

• Collaborating directly with engineering teams to secure design wins, address challenges, usher projects into production, and offer support through the project's lifecycle.

• Acting as a trusted advisor to our clients, understanding their environment and constraints, translating these into product requirements and solutions, and helping both them and NVIDIA anticipate and avoid potential issues.

What we need to see:

• 2+ years of experience in cloud computing and/or large-scale AI systems.

• A BS in EE, CS, Math, or Physics, or equivalent experience.

• A proven understanding of cloud computing and large-scale computing systems.

• Proficiency in Python, C, or C++ and experience with AI frameworks like Pytorch or TensorFlow.

• A passion for machine learning and AI, and the drive to continually learn and apply new technologies.

• Excellent interpersonal skills, including the ability to explain complex technical topics to non-experts.

Ways to stand out from the crowd:

• Recent projects or contributions (for example, on GitHub) related to large language models and transformer architectures.

• Knowledge of Azure cloud and AzureML services.

• Experience with CUDA programming and optimization.

• Familiarity with NVIDIA networking technologies such as Infiniband.

• Proficiency in Linux, Windows Subsystem for Linux, and Windows.