Job Description
Job Overview:
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s an outstanding legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is encouraged to do their best work. Come join the team and see how you can make a lasting impact on the world.
As a Senior Technical Marketing Engineer for AI Infrastructure, you will join a dedicated team that is passionate about delivering outstanding developer and user experiences on NVIDIA's enterprise and datacenter hardware and software products. This position in Santa Clara, CA, gives you the chance to collaborate with engineering, product, marketing and executive teams and contribute to the advancement of datacenter GPUs and large scale GPU computing systems.
What you will be doing:
Evaluate and run multi-node jobs on large clusters to assess performance and developer experience in distributed deep learning environments.
Understand and profile workloads for deep learning applications. Educate customers and tech press to run these workloads and benchmark NVIDIA data center systems for performance evaluations.
Conduct performance benchmarking of AI infrastructure with industry-standard models and frameworks (e.g., vLLM, PyTorch, TensorFlow) to measure throughput, latency, and scalability.
Engage with various teams across NVIDIA such as product, marketing, hardware, software engineering, and QA to improve NVIDIA's product offerings.
Develop developer-focused content, including detailed tutorials and code samples, to demonstrate the latest features in NVIDIA’s tools and libraries.
Write technical whitepapers, product briefs, and solution blueprints to highlight innovative use cases, architecture designs, and best practices in AI infrastructure.
Deliver live demos and technical presentations at leading industry events, such as the NVIDIA GPU Technology Conference (GTC), CES, SIGGRAPH, and other global conferences, showcasing cutting-edge NVIDIA technologies.
What we need to see:
A Bachelor’s or Master’s in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering or equivalent experience.
5+ years of experience.
Proficiency in Python and C++ for AI and HPC applications.
Experience using large scale multi node GPU infrastructure on premise or in CSPs
Background in deep learning model architectures and experience with Pytorch and large scale distributed training
Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture. Experience with NVIDIA's Infrastructure and software stacks.
Ways to stand out from the crowd:
Demonstrate proficiency in managing job scheduling, workload orchestration, and deploying multi-node GPU clusters using Slurm and Kubernetes.
Solid understanding of network protocols, distributed system communication, and high-speed interconnects (e.g., InfiniBand, RDMA, Ethernet) to optimize data flow across nodes in HPC environments.
Hands-on experience with NVIDIA GPUs, HPC storage, networking, and cloud computing.
With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most hard-working and dedicated people on the planet working for us and, due to unprecedented growth, our company is growing fast. If you're creative and autonomous with a genuine passion for technology, we want to hear from you.
The base salary range is 120,000 USD - 230,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
