This role pays more than
97%
of similar roles. Most pay
$149,467–$217,793
— the shaded band above.
At the midpoint, this role pays about
$290k
versus about
$184k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
896 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 876 roles with salary data.
As a Senior Product Dev Rel Engineer - DSX, you will join the Data Science & AI System Software platform team to improve developer experience across the DSX ecosystem. You will bridge the gap between external AI developers and internal engineering teams by synthesizing technical feedback into product roadmaps and crafting high-impact assets like deployment guides, containerized workflows, and reference architectures. Your daily work involves conducting system architecture reviews with partners, validating software releases against real-world workloads, and defining metrics for usability and documentation clarity. You will utilize a technical stack including Linux systems, Python, C++, GPU acceleration, Kubernetes, Docker, PyTorch, and CUDA. The role focuses on solving friction in deep learning software stacks, container runtimes, and system orchestration to accelerate the deployment of AI applications across multi-node GPU clusters and enterprise data platforms.
Translate technical feedback from AI practitioners and open-source communities into product management and engineering roadmaps.
Create high-impact technical assets including deployment guides, containerized workflows, reference architectures, and performance benchmarks.
Validate core software stack releases against real-world AI workloads before production launches.
Conduct technical deep-dives and architecture reviews with partners to remove friction and accelerate adoption of DSX components.
Define metrics for developer engagement regarding system usability, documentation clarity, and time-to-first-training run.
Represent NVIDIA as a technical authority at major conferences to build feedback loops and increase platform trust.
What we're looking for
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent experience.
12+ years of experience in Developer Relations, Systems Engineering, Technical Product Management, or Solutions Architecture.
Deep technical foundation in Linux systems, Python, C++, GPU acceleration, container orchestration (Kubernetes, Docker), and modern AI framework stacks (PyTorch, CUDA).
Experience guiding platform software and engineering priorities through 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 to influence product managers, engineers, and external technical leaders.
Experience with NVIDIA DSX, DGX systems, DGX Cloud, CUDA-X, or related NVIDIA deep learning software stacks (preferred).
Track record of open-source contributions in cloud-native or AI infrastructure space, such as Kubernetes, Kubeflow, Ray, vLLM, or Triton (preferred).
Remote (Santa Clara, CA)+18 days ago
$184,000–$287,500
Kubernetes
Python
Go
PyTorch
TensorFlow
CUDA
MLOps
Terraform
Ansible
Prometheus
Grafana
InfiniBand
RoCE
Triton
NeMo
CI/CD
Linux
Distributed Systems
NVIDIA Reference Architectures
MLOps
Python
C++
Go
Rust
Kubernetes
CUDA
NeMo
RAPIDS
Triton
NIM
InfiniBand
NVLink
RoCE
CI/CD
GitOps
Linux
Bash
Distributed Training
Inference Optimization
Product Engineering
CAD
Six Sigma
Project Management
DOE
Statistical Analysis
Technical Documentation
Design Control
Product Development
Mechanical Engineering