NVIDIA Logo

NVIDIA

Senior DGX Cloud AI Infrastructure Software Engineer

Reposted 2 Days Ago
Be an Early Applicant
In-Office or Remote
3 Locations
184K-357K Annually
Senior level
In-Office or Remote
3 Locations
184K-357K Annually
Senior level
The role involves developing and optimizing AI infrastructure for large-scale training and inference, ensuring system reliability and efficiency through software engineering practices.
The summary above was generated by AI

Joining NVIDIA's DGX Cloud AI Efficiency Team means contributing to the infrastructure that powers our innovative AI research. This team focuses on developing tools for optimizing efficiency and resiliency of AI workloads - pre-training, post-training, inference. Our objective is to deliver a stable, scalable environment for AI researchers, providing them with the necessary resources and scale to foster innovation. We are seeking an AI infrastructure software engineer to join our team. You'll 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, diverse, 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!

What you’ll be doing:

  • 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

What we need to see:

  • 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

 

NVIDIA leads the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. NVIDIA is looking for exceptional people like you to help us accelerate the next wave of artificial intelligence.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until February 6, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

C/C++
Elk
Ib Verbs
Jax
Libfabrics
Loki
Nccl
Prometheus
Python
PyTorch
Rdma
TensorFlow
Ucx
HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

Similar Jobs

7 Hours Ago
Remote or Hybrid
TX, USA
123K-204K Annually
Senior level
123K-204K Annually
Senior level
Automotive • Cloud • Greentech • Information Technology • Other • Software • Cybersecurity
The Senior Manager, Marketing Operations - Fleet leads integrated digital marketing strategies, manages a marketing team, and optimizes multi-channel marketing efforts while aligning messaging with business objectives.
Top Skills: Google AnalyticsSalesforce Marketing Cloud
7 Hours Ago
Remote or Hybrid
United States
112K-186K Annually
Senior level
112K-186K Annually
Senior level
Automotive • Cloud • Greentech • Information Technology • Other • Software • Cybersecurity
The Senior Manager drives operational excellence and financial integrity, leading cross-functional initiatives and mentoring teams to shape processes for growth. Responsible for complex systems integration and alignment with corporate objectives.
Top Skills: ExcelOffice ProductsOracleWorkamajig
7 Hours Ago
Remote or Hybrid
United States
17-25 Hourly
Junior
17-25 Hourly
Junior
Automotive • Cloud • Greentech • Information Technology • Other • Software • Cybersecurity
The Technical Customer Care Specialist will handle customer inquiries regarding technical issues with DealerTrack Software, work on problem resolution, and mentor team members to enhance client satisfaction.
Top Skills: Dealertrack Dealer Management SoftwareJava

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account