Systems Engineer Internships
Systems engineer internships give university students, recent graduates, and early-career switchers hands-on project experience, mentorship from working engineers, and, at many employers, a path toward a full-time offer. Openings are concentrated across Manufacturing, Technology & Software, and Consulting & Professional Services, with Tesla, RoviSys Building Technologies, and Together AI among the employers posting roles now.
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NVIDIA is a worldwide technology company headquartered in Santa Clara, California. NVIDIA manufactures graphics processing units (GPUs), as well as system on a chip units (SOCs) for the expanding markets. Our work in visual computing, the art and science of computer graphics, has led to thousands of patented inventions, breakthrough technologies, deep industry relationships and a globally recognized brand. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers inventions such as artificial intelligence and autonomous cars.
You would join the team responsible for the maintenance, development, and execution of Desktop Gaming Performance testing in Linux and Windows environments for the world's fastest, power efficient GPUs. This job has a preferred duration of 8-12 months.
What you'll be doing:
Writing and maintaining containerized GPU accelerated workloads for the financial services industry, from deep learning training and inference, to portfolio optimization and backtesting.
Running, validating, and analyzing benchmarking models at scale on HPC clusters.
Visualizing performance data, building charts and dashboards using internal schemas and tooling.
Working closely with the latest and greatest in financial AI models and tooling to help build reference models for NVIDIA.
What we need to see:
Enrolled in a Bachelors program majoring in Computer Engineering, Software Engineering, Computer Science, or related field.
Desire to improve code quality by learning and applying computer science fundamentals, algorithms, and data structures.
Comfort with teamwork, collaboration, and a desire to reach across functional borders to develop new partnerships.
Active experience with Python.
Working comfort in a Linux command-line environment with version control.
Foundational understanding and interest of the machine learning lifecycle (training, evaluation, and inference).
Ways to stand out from the crowd:
Familiarity with PyTorch and/or training, testing, and evaluating machine learning models.
Experience with GPU computing or CUDA and libraries like cuOPT, CUTLASS, cuDNN, etc.
Exposure to workload orchestration and job schedulers (Kubernetes, Slurm).
Experience with containerized applications and resource management.
Interest in quantitative finance and applying performance data to real-world problems.
You will also be eligible for Intern benefits.
Applications for this job will be accepted at least until July 10, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.NVIDIA is a worldwide technology company headquartered in Santa Clara, California. NVIDIA manufactures graphics processing units (GPUs), as well as system on a chip units (SOCs) for the expanding markets. Our work in visual computing, the art and science of computer graphics, has led to thousands of patented inventions, breakthrough technologies, deep industry relationships and a globally recognized brand. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers inventions such as artificial intelligence and autonomous cars.
You would join the team responsible for the maintenance, development, and execution of Desktop Gaming Performance testing in Linux and Windows environments for the world's fastest, power efficient GPUs. This job has a preferred duration of 8-12 months.
What you'll be doing:
Writing and maintaining containerized GPU accelerated workloads for the financial services industry, from deep learning training and inference, to portfolio optimization and backtesting.
Running, validating, and analyzing benchmarking models at scale on HPC clusters.
Visualizing performance data, building charts and dashboards using internal schemas and tooling.
Working closely with the latest and greatest in financial AI models and tooling to help build reference models for NVIDIA.
What we need to see:
Enrolled in a Bachelors program majoring in Computer Engineering, Software Engineering, Computer Science, or related field.
Desire to improve code quality by learning and applying computer science fundamentals, algorithms, and data structures.
Comfort with teamwork, collaboration, and a desire to reach across functional borders to develop new partnerships.
Active experience with Python.
Working comfort in a Linux command-line environment with version control.
Foundational understanding and interest of the machine learning lifecycle (training, evaluation, and inference).
Ways to stand out from the crowd:
Familiarity with PyTorch and/or training, testing, and evaluating machine learning models.
Experience with GPU computing or CUDA and libraries like cuOPT, CUTLASS, cuDNN, etc.
Exposure to workload orchestration and job schedulers (Kubernetes, Slurm).
Experience with containerized applications and resource management.
Interest in quantitative finance and applying performance data to real-world problems.
You will also be eligible for Intern benefits.
Applications for this job will be accepted at least until July 10, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.Systems Engineer Internship Market
Who's Hiring
- Tesla11
- RoviSys Building Technologies4
- Together AI2
- Serco1
- NVIDIA1
Top Industries Hiring
- Manufacturing10
- Technology & Software7
- Consulting & Professional Services5
- Education1
- Distribution & Wholesale1
Tips for Your Systems Engineer Internship Search
Start your search in the fall for summer roles
Large aerospace, defense, and technology employers recruit summer systems engineer interns the preceding fall, with some application windows closing in October or November. Smaller companies and co-op programs post closer to their start dates, so checking the listings regularly throughout the year covers both recruiting cycles.
Build a portfolio that shows systems-level work
Without an extensive work history, documented projects are your strongest credential. Put together two or three completed projects that demonstrate requirements analysis, architecture decisions, or integration work, include the tools you used, what problem you solved, and a link to code repositories or technical write-ups recruiters can review.
Work your campus network and apply directly at the same time
Campus career fairs surface structured programs tied to your university, and professors or career center staff often know which employers recruit from your school before roles post publicly. Applying directly to companies running smaller cohorts alongside campus activity widens the pool you reach and catches openings that never appear on university job boards.
Practice your technical screen out loud before you apply
Systems engineer intern interviews typically involve a technical screen covering systems design, requirements decomposition, or trade-off analysis, some roles add a software or controls component. Practice explaining your reasoning as you work through problems, not just arriving at an answer, since interviewers weigh how you think as much as the final solution.
Target structured internship programs built for new engineers
Many large employers run cohort or rotational programs specifically designed to develop early-career systems engineers, rotating interns through multiple teams or domains across a single summer. These programs recruit early and fill fast, so identify the ones that fit your background and apply in the first wave rather than waiting for a second round.
Set your work-type filter before you start
On-site roles are 95% of the systems engineer internships listed here. Decide what you can realistically commit to, relocation, a local commute, or fully remote, before you start sorting through listings. Filtering by location and work type up front on Migrate Mate saves time and keeps you focused on roles you can actually accept.
Systems Engineer Internships: Frequently Asked Questions
How do I get a systems engineer internship?
Lead with coursework and personal projects rather than work history, hiring teams expect limited professional experience at the intern level. A portfolio of documented systems or integration projects gives recruiters something concrete to assess. Combine direct applications to companies running smaller cohorts with campus career fairs, where recruiters often move faster for students they meet in person.
Can a systems engineer internship turn into a full-time job?
Many employers extend return offers to strong interns, but conversion is never guaranteed. What actually drives it is your performance on real project work, whether the team has open headcount at the end of your term, and how early you signal interest in returning. Position for a return offer by delivering on your assigned work, but keep applying to other roles in parallel.
When should I apply for systems engineer internships?
Earlier than most students expect. Large defense contractors, aerospace firms, and tech companies recruit summer interns the preceding fall, often with deadlines in October or November. Smaller companies and co-op programs post closer to their start dates, so openings appear year-round, checking regularly rather than waiting for a single recruiting season covers both cycles.
Are systems engineer internships paid?
Most professional systems engineer internships in the U.S. are paid. Compensation varies by company size, industry, and location, and listings show it where the employer chooses to disclose it. Unpaid internships exist but are uncommon at established technology, defense, and engineering employers.
What should a systems engineer internship resume include?
Lead with projects, not work history. Include two or three complete, documented projects that show systems integration, requirements analysis, or architecture work, list the tools and frameworks used and link to any supporting code repositories, technical write-ups, or design artifacts. Add relevant coursework in systems engineering, controls, or software, and keep the whole resume to one page.
Are there remote systems engineer internships?
Yes. Remote and hybrid roles make up 5% of the systems engineer internship listings here, with the rest on-site. Remote cohorts tend to fill fast, so apply early and filter by work type to see them before they close.
Can international students get systems engineer internships?
Yes. F-1 students can intern through CPT while enrolled or through OPT work authorization after finishing a degree, and the employer does not have to file anything for either, so many companies are open to international interns. Confirm your eligibility and timing with your university's international student office before accepting an offer.
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