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Internship Embedded System Software Engineer Jobs in Raleigh, NC

Baxter

Principal Engineer, Embedded Systems

Raleigh, NC

$112K - $154K/yr

Broad understanding of software engineering best practices, embedded systems, and standard development methodologies. * Proficiency with development and CI tools (e.g., Visual Studio/Eclipse, Git ...

Parker

Senior Embedded Software Engineer

Cary, NC · Hybrid

$121K - $159K/yr

Position Summary Parker Lord Electromechanical Systems (EMS) is seeking an experienced Embedded Software Engineer to develop and verify software for control systems used in demanding aerospace and ...

Trimm Inc.

Embedded Design Engineer

Youngsville, NC · On-site

$85K - $115K/yr

In this role, you will play a key part in designing cutting-edge embedded systems for new products ... software packages a plus. · Ability to communicate technical specifications and standards to ...

Trimm Inc.

Embedded Design Engineer

Youngsville, NC · On-site

$85K - $115K/yr

In this role, you will play a key part in designing cutting-edge embedded systems for new products ... Familiarity with CAD and Circuit Design software packages a plus. Ability to communicate technical ...

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All JobsInternship Embedded System Software Engineer JobsInternship Embedded System Software Engineer Jobs in Raleigh, NC

Internship Embedded System Software Engineer information

See Raleigh, NC salary details

$68K

$149.1K

$169.1K

How much do internship embedded system software engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for internship embedded system software engineer in Raleigh, NC is $149,101.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,800.00 and $168,200.00 per year, depending on experience, location, and employer.

What is the difference between Internship Embedded System Software Engineer vs Embedded System Software Engineer?

AspectInternship Embedded System Software EngineerEmbedded System Software Engineer
QualificationsEnrolled in or recent graduate of relevant degree (e.g., Electrical Engineering, Computer Science)Bachelor's or higher in related field, with some experience
Work EnvironmentInternship programs, entry-level projects, supervised tasksFull-time professional role, independent project work
ResponsibilitiesAssisting in development, learning, supporting senior engineersDesigning, developing, testing embedded software independently
Industry UsageInternship programs, training, entry-level hiringFull-time employment in electronics, automotive, IoT sectors

The main difference between an Internship Embedded System Software Engineer and an Embedded System Software Engineer lies in experience, responsibilities, and employment status. Internships are designed for students or recent graduates gaining initial industry exposure, while full-time engineers handle independent projects and advanced tasks.

What are the most commonly searched types of Embedded System Software Engineer jobs in Raleigh, NC? The most popular types of Embedded System Software Engineer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Internship Embedded System Software Engineer jobs? Cities near Raleigh, NC with the most Internship Embedded System Software Engineer job openings:
Internship Embedded System Software Engineer jobs near you
System Software Engineer - Data Center GPU Compute Diagnostics

System Software Engineer - Data Center GPU Compute Diagnostics

Nvidia

Durham, NC

$167K - $198K/yr

Full-time

Posted 28 days ago

Job description

We are seeking a system software engineer to work on next-generation Data Center GPU diagnostics for rack-scale AI supercomputer systems. Our charter is to build applications and compute workloads that test and heavily stress GPU compute engines, HBM memory, cache hierarchy, PCIe/NVLinkinterfaces, power delivery, and thermal behavior, and to use those applications in silicon/system bring-up along with packaging such tools for manufacturing and customer use. In this role you will partner with a senior engineer leading the team's CUDA kernel and GEMM diagnostics work, owning well-scoped pieces of the codebase end-to-end while ramping on GPU microarchitecture and silicon characterization. The best candidates will have experience writing low-level diagnostic, performance, or stress software for complex hardware systems, ideally including experience with GPUs, CUDA kernels, GEMM-style workloads, CPUs,NICsor high-speed interconnects such as PCIe.

Good interpersonal skills arerequiredas this role will involve close collaboration with hardware architecture, silicon validation,manufacturingand field teams. In addition, the engineer will grow their knowledge of operating systems, computer architecture, GPU memory, voltage/frequency behavior, thermal limits, high-speed buses, and modern AI development and analysis tools to efficientlyvalidateand test next-generation processors and systems.Join an exciting,rewardingandfast pacedenvironment!

Whatyou'llbe doing:

  • Working closely with hardware architecture, driver, manufacturing, and field teams through the product development lifecycle of rack-scale AI systems.

  • Implementing andmaintainingCUDA/C++ diagnostic workloads and software infrastructure used in chip development, validation, productization, and field triage.

  • Writing and tuning GPU compute tests that stress Tensor Cores, SMs, L2/cache hierarchy, HBM memory, and related power/thermal operating points.

  • Implementing and tuning GEMM-style diagnostic workloads, including tests combined withadditionalloadinNVLink,PCIe or CPU subsystems.

  • Contributing to higher-level AI workload tests, includingPyTorch-based large model workloads that stress GPUs, memory, interconnects, thermals, and system software under realistic rack-scale AI use cases.

  • Bringing up andvalidatingnew hardware features with pre-beta GPU drivers, low-level diagnostic software, and system telemetry, under guidance from the technical lead.

  • Triaging and debugging failures involving ECC, HBM behavior, thermal limits, voltage/frequency margining, and PCIe/NVLinkerrors.

What we need to see:

  • BS or MS degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.

  • 5+ years of system software, GPU software, embedded software, or hardware validation experience.

  • Experience writing low-level diagnostics, interacting with device firmware and hardware level debuggers.

  • Strong C/C++ and Python programming skills.

  • Exposure to GPU architecture, CUDA kernels, GPU compute workloads, or related accelerator programming is strongly preferred.

  • Working knowledge of memory systems, ECCbehaviorandDMAengines.

  • Familiarity with GEMM-styleworkloads.

  • Awareness of voltage/frequency characterization, thermal testing, power stress, or related silicon validation concepts such asVmin/Fmax and P-state testing.

  • Experience using modern AI development and analysis tools to improve engineering velocity, including code development, debugging, and test creation.

  • Strong problem solving and low-level debugging skills.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 24, 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.
Nvidia logo

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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