Senior DGX Cloud AI Infrastructure Software Engineer

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CAAustin, TXRedmond, WA
Salary: $184,000–$287,500 / yr
Posted: 162 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 $193k

This role $236k

$133k most similar roles pay here $304k

This role pays more than 78% of similar roles. Most pay $149,462–$235,750 — the shaded band above. At the midpoint, this role pays about $236k versus about $193k 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 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Senior DGX Cloud AI Infrastructure Software Engineer

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As a Senior DGX Cloud AI Infrastructure Software Engineer on the DGX Cloud AI Efficiency Team, you will develop infrastructure software and tools to support large-scale pre-training, post-training, and inference. You will be responsible for building and maintaining systems that ensure high efficiency and availability while co-designing APIs for integration with resiliency stacks. Your daily work involves optimizing libraries, defining reliability metrics, and performing root cause analysis on failures from the application level down to the hardware level. The role requires proficiency in Python, C/C++, and various scripting languages, alongside experience with observability platforms like ELK, Prometheus, or Loki. You will also utilize technologies such as RDMA stacks including NCCL, IB verbs, ucx, and libfabrics while working with deep learning frameworks like PyTorch, TensorFlow, JAX, and Ray to solve complex infrastructure challenges.

Skills

Python C/C++ PyTorch TensorFlow JAX Ray RDMA NCCL Prometheus ELK Loki CI Distributed Systems High-Performance Computing

What you'll do

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

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).
Proficiency in programming languages such as Python, C/C++, and various scripting languages.
Experience building and scaling large-scale distributed systems.
Experience with AI training and inferencing infrastructure services.
Strong debugging skills to analyze and triage failures from the application level down to the hardware level.
Experience with observability platforms for monitoring and logging such as ELK, Prometheus, or Loki.
Knowledge of quality software engineering practices including test development, defensive programming, version control, and CI.

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