Senior AI Infrastructure Software Engineer - DGX Cloud

NVIDIA•Us, CA

12d•Hybrid

About The Position

Joining NVIDIA's DGX Cloud Lepton Team means contributing to the leading cloud product that powers innovative AI research and developers. We focus on building the AI/ML platform for improving productivity, optimizing efficiency and resiliency of AI workloads, as well as developing scalable AI infrastructure services globally. We are seeking an AI infrastructure software engineer to join our team. You'll be instrumental in designing, building, and maintaining AI platforms that enable large-scale AI training, inferencing, fine-tuning, and Agentic AI in production. 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 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. If you are seeking an exciting and rewarding career that makes a difference, we invite you to apply now!

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.
Familiar in Kubernetes and operating large-scale observability platforms for monitoring and logging (e.g., ELK, Prometheus, Loki).
Proficiency in programming languages such as Python, C/C++, script languages
Excellent communication and collaboration skills, and a culture of diversity, intellectual curiosity, problem solving, and openness are essential.

Nice To Haves

Experience in working with the large scale AI cluster and cloud-native infrastructure
Strong understanding of NVIDIA GPUs, network technologies (RDMA, IB, NCCL)
Good understanding on DL frameworks internal PyTorch, TensorFlow, JAX, Dynamo, and Ray
Experience and root cause analysis of failures and datacenter scale
Strong background in software design and development.

Responsibilities

Develop platform and tools for large-scale AI, LLM, and GenAI infrastructure.
Develop and optimize tools to improve AI/ML workload efficiency and resiliency.
Root cause and 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 on the platform.
Define meaningful and actionable reliability metrics to track and improve system and service reliability.
Skilled in problem-solving, root cause analysis, and optimization.