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Internship Infrastructure Software Engineer Jobs

Nvidia

OR · On-site

$108K - $147K/yr

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 ...

Apple

Senior Infrastructure Software Engineer

Cupertino, CA · On-site

$133K - $182K/yr

... infrastructure transformations in the industry. We operate at a scale few engineers ever encounter ... You are someone with ideas and real passion for software delivered as a service to improve reuse ...

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Internship Infrastructure Software Engineer information

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How much do internship infrastructure software engineer jobs pay per hour?

As of Jul 4, 2026, the average hourly pay for internship infrastructure software engineer in the United States is $25.42, according to ZipRecruiter salary data. Most workers in this role earn between $20.67 and $28.85 per hour, depending on experience, location, and employer.

What is the difference between Internship Infrastructure Software Engineer vs Infrastructure Software Engineer?

AspectInternship Infrastructure Software EngineerInfrastructure Software Engineer
Required CredentialsTypically pursuing or recently completed a relevant degree; no professional experience requiredBachelor's or higher in Computer Science or related field; professional experience preferred
Work EnvironmentInternship programs, entry-level projects, supervised tasksFull-time roles, independent project management, team collaboration
Employer & Industry UsageTech companies, startups, IT departments during internship periodsEstablished companies, data centers, cloud providers, large-scale IT infrastructure

The main difference is that an Internship Infrastructure Software Engineer is an entry-level position designed for students or recent graduates gaining initial industry experience, while an Infrastructure Software Engineer is a full-time professional responsible for designing, implementing, and maintaining infrastructure systems. Interns typically work under supervision, whereas full-time engineers handle complex projects independently.

What cities are hiring for Internship Infrastructure Software Engineer jobs? Cities with the most Internship Infrastructure Software Engineer job openings:
What are the most commonly searched types of Infrastructure Software Engineer jobs? The most popular types of Infrastructure Software Engineer jobs are:
Internship Infrastructure Software Engineer jobs near you
Infographic showing various Internship Infrastructure Software Engineer job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 92% Full Time, 6% Part Time, and 1% Temporary. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $52,867 per year, or $25.4 per hour.
Senior DGX Cloud AI Infrastructure Software Engineer

Senior DGX Cloud AI Infrastructure Software Engineer

Nvidia

Austin, TX • On-site

$107K - $146K/yr

Full-time

Posted yesterday

Job description

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 April 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.
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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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