Senior Full-Stack Software Engineer

Nvidia•Seattle, WA

32d

About The Position

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we're at the forefront of AI innovation powering breakthroughs in research, autonomous vehicles, robotics, and more. The DGX Cloud team builds and operates the AI infrastructure that fuels this progress. We're looking for a Senior Full-Stack Software Engineer to join our DGX Cloud AI Infrastructure team and help deliver the next-generation user experience for NVIDIA's GPU clusters and AI infrastructure. In this role, you'll design and build a unified, self-service portal that serves as the front door to our AI compute platform enabling researchers to efficiently manage, monitor, and optimize their use of GPU clusters. You'll work across the stack to build intuitive interfaces, streamline workflows, and surface actionable insights that improve the productivity of AI research teams across the company.

Requirements

8+ years of experience in developing software infrastructure for large scale AI systems.
Bachelor's degree or higher in Computer Science or a related technical field (or equivalent experience).
Proficiency with full-stack development: JavaScript (Vue or React), Node.js, Python, and/or Golang, script languages
Experience with distributed systems and cloud-native technologies (Docker, Kubernetes, microservices)
Familiarity with observability stacks: ELK, OpenSearch, Prometheus, Grafana, or Loki
Strong debugging and root cause analysis skills across application and infrastructure layers
Experience with large-scale AI training, inference, or data infrastructure services
Excellent communication, collaboration, problem solving and a growth mindset

Nice To Haves

Experience building developer platforms or self-service internal infrastructure tools for efficiency, resiliency, or observability.
Hands-on experience as a Machine Learning Engineer (MLE) or deep familiarity with DL frameworks (e.g., PyTorch, TensorFlow, JAX, Ray).
Hands-on experience operating at datacenter scale, including GPU cluster debugging and root cause analysis.
Experience with MongoDB, Hadoop, or Spark.

Responsibilities

Design, develop, and deploy full-stack web applications to support large-scale AI infrastructure operations and workflows
Collaborate with AI and ML research teams to identify pain points and deliver tools that accelerate their work
Develop APIs, backend services, and UIs to improve visibility, observability, and control over large-scale GPU clusters
Develop backend services to manage job schedulers and cluster operations.
Define and track metrics that measure efficiency, resiliency, and developer productivity across the platform
Drive engineering excellence in testing, CI/CD, code quality, and performance
Lead architectural discussions and mentor junior engineers on design and implementation
Stay ahead of AI/ML infrastructure trends and drive adoption of best practices within the team