Senior DGX Cloud AI Infrastructure Software Engineer

Details

Joining NVIDIA's DGX Cloud AI Efficiency Team means contributing to the infrastructure that powers our innovative AI research. This team focuses on optimizing efficiency and resiliency of AI workloads, as well as developing scalable AI and data infrastructure tools and services. Our objective is to deliver a stable, scalable environment for AI researchers, providing them with the necessary resources and scale to foster innovation.

You will be instrumental in designing, building, and maintaining AI infrastructure that enable large-scale AI training and inferencing. The responsibilities include implementing software and systems engineering practices to ensure high efficiency and availability of AI systems.

As a senior DGX Cloud AI Infrastructure software engineer at NVIDIA, you will have the opportunity to work on innovative technologies that power the future of AI and data science, and be part of a dynamic and supportive team that values learning and growth. The role provides the autonomy to work on meaningful projects with the support and mentorship needed to succeed, and contributes to a culture of blameless postmortems, iterative improvement, and risk-taking.

Responsibilities

• Develop infrastructure software and tools for large-scale AI, LLM, and GenAI infrastructure.
• Develop and optimize tools to improve infrastructure efficiency and resiliency.
• Root cause, analyze, and triage failures from the application level to the hardware level.
• Enhance infrastructure and products underpinning NVIDIA's AI platforms.
• Co-design and implement APIs for integration with NVIDIA's resiliency stacks.
• Define meaningful and actionable reliability metrics to track and improve system and service reliability.
• Apply strong problem-solving, root cause analysis, and optimization skills.

Requirements

• Minimum of 12+ 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).
• Strong debugging skills and experience in analyzing and triaging AI applications from the application level to the hardware level.
• Proven track record in building and scaling large-scale distributed systems.
• Experience with AI training and inferencing and data infrastructure services.
• Familiarity operating large-scale observability platforms for monitoring and logging (examples provided: ELK, Prometheus, Loki).
• Proficiency in programming languages such as Python and C/C++, and scripting languages.
• Excellent communication and collaboration skills; culture of diversity, intellectual curiosity, problem solving, and openness are essential.

Ways to stand out

• Experience working with large-scale AI clusters.
• Strong understanding of NVIDIA GPUs and network technologies (RDMA, InfiniBand, NCCL).
• Good understanding of deep learning frameworks (internal PyTorch, TensorFlow, JAX) and Ray.
• Experience in root cause analysis of failures at datacenter scale.
• Strong background in software design and development.

Compensation & Other Details

• Base salary ranges (determined based on location, experience, and comparable pay):
  • Level 5: 224,000 USD - 356,500 USD
  • Level 6: 272,000 USD - 425,500 USD
• You will also be eligible for equity and benefits.
• Applications for this job will be accepted at least until July 29, 2025.

NVIDIA leads the way in developments in Artificial Intelligence, High-Performance Computing, and Visualization. NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.