Collaborating across departments including DSX Engineering, DGX Cloud, Solution Architecture, and Developer Marketing to steer early-access (EA) programs and validate core DSX software stack releases against real-world AI workloads prior to production launches.
Conducting technical deep-dives and system architecture reviews with strategic ISV partners, enterprise AI engineering teams, and cloud platform providers to remove friction and accelerate adoption of DSX components.
Defining measurements for developer engagement within DSX that track system software usability, setup ergonomics, driver/runtime integration, documentation clarity, and time-to-first-training run.
Representing NVIDIA DSX as a technical authority at major AI, cloud-native, and developer conferences, building strong feedback loops that increase platform velocity and developer trust.
What we need to see
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent experience.
12+ years of proven experience in Developer Relations, Systems Engineering, Technical Product Management, or Solutions Architecture passionate about enterprise AI infrastructure, cloud platforms, or developer platforms.
Deep technical foundation in Linux systems, Python, C++, GPU acceleration, container orchestration (e.g., Kubernetes, Docker), and modern AI framework stacks (e.g., PyTorch, CUDA).
Established experience in guiding platform software and engineering priorities through detailed developer research, infrastructure troubleshooting, and product feedback loops.
Hands-on experience building, deploying, or optimizing enterprise data science environments, containerized AI workloads, or distributed deep learning pipelines.
Strong cross-functional leadership and communication skills, with a demonstrated history of influencing product managers, core software engineers, and external technical leaders without direct authority.
Ways to stand out from the crowd
Direct experience with NVIDIA DSX, DGX systems, DGX Cloud, CUDA-X, or related NVIDIA deep learning system software stacks.
Proven track record of open-source contributions or maintainer roles in the cloud-native or AI infrastructure space (e.g., Kubernetes, Kubeflow, Ray, vLLM, Triton).
Deep understanding of enterprise AI cluster operations, multi-node GPU scaling, telemetry/observability tools, and high-performance interconnects (e.g., InfiniBand, NVLink).
Experience building or expanding a Product DevRel or Developer Experience (DX) function within a cloud infrastructure or enterprise platform organization.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you consider your future, explore what we provide for you and your family at www.nvidiabenefits.com/
#Hybrid-LI
- Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
- 224,000 USD – 356,500 USD for Level 5; and 272,000 USD – 431,250 USD for Level 6.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.
