Senior AI Infrastructure Engineer - Scalable ML Platform + Equity

NVIDIA AI; Seattle (WA); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking an AI infrastructure software engineer to design, build, and maintain scalable AI platforms enabling large-scale training, inference, and GenAI workloads. You will work on platform tooling, APIs, and resiliency stacks with a focus on reliability and performance.

Join a team that values learning, blameless postmortems, and iterative improvement while collaborating across cross-functional teams to deliver production-ready infrastructure for cutting-edge AI workloads.

Qualifications

• 8+ years of experience building software infrastructure for large-scale AI systems.
• BS or higher in CS or a related technical field or equivalent experience.
• Strong debugging and triage skills across software and hardware levels.

Responsibilities

• Develop platform and tools for large-scale AI, LLM, and GenAI infrastructure.
• Optimize tools to improve AI/ML workload efficiency and resiliency.
• Root-cause analysis from application to hardware level.
• Enhance infrastructure and products underpinning NVIDIA's AI platforms.
• Co-design and implement APIs for resiliency stacks on the platform.
• Define meaningful reliability metrics to track system and service reliability.
• Demonstrate strong problem-solving and optimization skills.

Skills

Distributed systems

Kubernetes

Golang

Python

C/C++

Debugging

System design

Communication

Education

Bachelor's degree or higher in CS or related field

Tools

ELK

Prometheus

Loki

Job description

NVIDIA is seeking an AI infrastructure software engineer to design, build, and maintain scalable AI platforms enabling large-scale training, inference, and GenAI workloads. You will work on platform tooling, APIs, and resiliency stacks with a focus on reliability and performance.

Join a team that values learning, blameless postmortems, and iterative improvement while collaborating across cross-functional teams to deliver production-ready infrastructure for cutting-edge AI workloads.