Nvidia Senior Full-Stack Software Engineer 

United States, Texas 

256977468

What You’ll Be Doing:

• 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

What We Need To See:

• 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

Ways to Stand Out from the crowd:

• 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.