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# Senior DGX Cloud AI Infrastructure Software Engineer

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $184,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Cloud Computing, Data Centers, Software Debugging, Distributed Systems, Python (Programming Language), Remote Direct Memory Access, Tensorflow, Prometheus, Software Engineering, AI Infrastructure, Data Logging, Pytorch, AI Platforms, Script Language, Information Technology, Software Version Control
- **Published:** May 24, 2026
- **Apply:** https://arc.dev/remote-jobs/j/nvidia-senior-dgx-cloud-ai-infrastructure-software-engineer-mbzfp86pbt

## About the Role

* 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).
 * 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).
 * 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++, script languages
 * Experience in quality software engineering practices, including test development, defensive programming, version control, and CI.
 * Excellent communication and collaboration skills, and a culture of diversity, intellectual curiosity, problem solving, and openness are essential.

Ways To Stand Out From The Crowd

 * Background in working with the large scale clusters
 * Experience in defining and building observability and telemetry software stack
 * Experience with RDMA software stack (NCCL, IB verbs, ucx, libfabrics)
 * Experience and root cause analysis of failures and datacenter scale
 * Good understanding on DL frameworks internal PyTorch, TensorFlow, JAX, and Ray

## Description

* Develop infrastructure software and tools for large-scale pre-training, post-training, and inference.
 * Develop and optimize tools and libraries to improve infrastructure efficiency and resiliency.
 * Co-design and implement APIs for integration with NVIDIA's resiliency stacks.
 * Enhance infrastructure and products underpinning NVIDIA's AI platforms.
 * Define meaningful and actionable reliability metrics to track and improve system and service reliability.
 * Skilled in problem-solving, root cause analysis, and optimization.
 * Root cause and analyze and triage failures from the application level to the hardware level


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