Nvidia Compute Architect Intern - 

United States, Texas 

534960417

What you’ll be doing:

• A considerable part of the day-to-day job is staying up to date on pioneering High Performance Computing, Deep Learning and Machine Learning ecosystems. You'll be called on to help architect and scale high-performance, distributed AI infrastructure on-prem or in the cloud built with the latest NVIDIA GPU supercomputers for new and existing customers.

• Address and resolve problems starting from the bare metal level, all the way up to the operating system, software stack, and application level.

• Share knowledge with different teams by delivering demos, assisting with proof-of-concepts, and writing papers and developer blogs. By collaborating with executives and engineering, address sophisticated problems and help bring NVIDIA's premiere technologies to life in the cloud and in the datacenter.

• Work directly with developers and hardware architects to debug cluster performance issues, identify new requirements, and improve workflows.

• Will be engaged by the account team when extra analysis is required in debugging customer issues.

• Provide additional expertise to enable the account team to be more adaptable to the customer and product engineering to get more actionable data at speed of light making them more efficient.

• Building custom product demonstrations and POCs for solutions that address critical business needs of our customers.

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 NVIDIA and/or accelerated computing technologies.

• Platform level understanding of server architecture, PCIe topology, GPUs, NICs, Linux OS and kernel drivers.

• Networking experience, including knowledge of Ethernet, InfiniBand or other networking protocols.

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

• SLURM, Kubernetes, and/or other job scheduler use, deployment, and debugging skills.

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

• Effective time management and capable of balancing multiple tasks.

• Strong analytical and problem-solving skills.

• Strong communication skills, both written and verbal, with the ability to collaborate and coordinate efficiently across multi-functional teams in engineering, sales, marketing, product, and program management.

Ways to stand out from the crowd:

• Demonstrated Communication Collectives (NCCL) experience.

• Excellent customer-facing skills and background.

• Platform design engineering, coding and proficient debugging skills including experience in C/C++, Linux kernel, virtualization and drivers,profilers/performanceanalysis tools (NSys).

• Familiarity with NVIDIA systems/SDKs (e.g. CUDA), NVIDIA Networking technologies (e.g., RoCE, InfiniBand), Switch interconnects and/or ARM CPU solutions through hands-on experience.

• Understanding of Deep Learning and Machine Learning frameworks (TensorFlow or PyTorch), LLM, MLOps, DevOps, and workflows applying cloud technologies, using Docker/containers, Kubernetes, cloud APIs, and data center deployments, among others.

We make extensive use of conferencing tools, but occasional travel is required for a local on-site visit to customers and data science conferences.