Senior DGX Cloud AI Infrastructure Software Engineer

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CAAustin, TXORWARedmond, WA
Salary: $184,000–$287,500 / yr
Employment: Full-time
Posted: 28 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $198k

This role $236k

$146k $303k

below market most similar roles pay here above market

This role pays more than 78% of similar roles. Most pay $160,912–$235,750 — the blue band above. At the midpoint, this role pays about $236k versus about $198k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

Most-posted roles

View all roles at Nvidia

At a glance

TL;DR · Senior DGX Cloud AI Infrastructure Software Engineer

Role Posting Log in to save

The Senior DGX Cloud AI Infrastructure Software Engineer joins the DGX Cloud AI Efficiency Team to develop infrastructure software and tools for large-scale pre-training, post-training, and inference. The role involves designing, building, and maintaining systems that ensure high efficiency and availability for AI workloads. Key responsibilities include optimizing tools and libraries for resiliency, co-designing APIs for integration with resiliency stacks, and defining actionable reliability metrics. The engineer must perform root cause analysis and triage failures from the application level down to the hardware level. Required skills include proficiency in Python, C/C++, and script languages, alongside experience with observability platforms like ELK, Prometheus, and Loki. Candidates should possess expertise in distributed systems, RDMA software stacks, and deep learning frameworks like PyTorch, TensorFlow, JAX, and Ray.

Skills

Python C/C++ PyTorch TensorFlow JAX Ray Distributed Systems RDMA NCCL IB Verbs UCX Libfabrics Prometheus ELK Loki CI Version Control High-Performance Computing APIs

What you'll do

Develop infrastructure software and tools for large-scale AI pre-training, post-training, and inference.
Optimize tools and libraries to improve the efficiency and resiliency of AI infrastructure.
Co-design and implement APIs for integration with NVIDIA's resiliency stacks.
Enhance the infrastructure and products underpinning NVIDIA's AI platforms.
Define and track actionable reliability metrics to improve system and service performance.
Perform root cause analysis and triage failures from the application level down to the hardware level.
Implement software and systems engineering practices to ensure high availability of AI systems.

What we're looking for

Minimum of 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).
Proven track record in building and scaling large-scale distributed systems.
Experience with AI training and inferencing infrastructure services.
Proficiency in programming languages such as Python, C/C++, and script languages.
Experience in quality software engineering practices, including test development, defensive programming, version control, and CI.
Strong debugging skills and experience in analyzing and triaging AI applications from the application level to the hardware level.
Experience with observability platforms for monitoring and logging (e.g., ELK, Prometheus, Loki).

Save