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Intern, R&D Graduate Year-Round - Smart Electronics Software - Hybrid

Job in Albuquerque, Bernalillo County, New Mexico, 87101, USA
Listing for: Sandia National Laboratories
Full Time, Part Time, Apprenticeship/Internship position
Listed on 2026-10-20
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Embedded Systems/ Firmware/ IoT, Embedded Software Engineer, Software Engineer
Salary/Wage Range or Industry Benchmark: 34000 - 48000 USD Yearly USD 34000.00 48000.00 YEAR
Job Description & How to Apply Below

Job

699406

Location

Albuquerque, NM

Full/Part Time

Part-Time

Regular/Temporary

Temporary

What Your Job Will Be Like

We are seeking a Year Round - R&D Graduate Intern to join our dynamic team!

On any given day, you may be called on to:

  • Develop, test, and integrate high-TRL software for embedded, electronics, and FPGA platforms.
  • Apply agentic coding tools and AI-assisted development methods to improve software productivity, quality, and maintainability.
  • Implement AI, machine learning, and autonomy algorithms for real-time execution on resource-constrained hardware.
  • Collaborate with electronics, firmware, software, systems, and mission-domain experts to develop integrated solutions.
  • Optimize algorithms and software for performance, latency, power, memory, and reliability constraints.
  • Support hardware-in-the-loop testing, embedded platform bring-up, verification, validation, and fieldable prototype demonstrations.
  • Contribute to software architectures, development workflows, and best practices for trusted AI-enabled embedded systems.
  • Explore emerging tools and methodologies for applying generative AI and autonomous coding agents to mission software development.

This position is ideal for someone who enjoys working at the intersection of modern software engineering, embedded systems, FPGA development, artificial intelligence, and national security applications. You will have the opportunity to shape how next-generation intelligent systems are developed and deployed on advanced electronics platforms.

The selected applicant can work a combination of onsite and offsite work. The selected applicant must live within a reasonable distance for commuting to the assigned work location when necessary.

Salary Range

At Sandia, we value the important work done by our interns and its contribution to National Security. Because of this, our interns earn competitive pay rates. Our pay structure is based on earned credit hours, classification, and degree level. Your pay rate will be determined during the hire process and included in your offer package. You can view the Intern Pay Rate chart here.

Qualifications

We Require

You bring the confidence and skills to be eligible for the job by meeting these minimum requirements:

  • Earned bachelor's degree
  • Currently attending and enrolled full time in an accredited science, engineering, or math graduate program
  • Minimum cumulative GPA of 3.0/4.0
  • Ability to work up to 30 hours per week during the academic year, and up to 40 hours per week during the summer
  • Ability to secure and maintatin a U.S. security clearance which requires U.S. citizenship
Qualifications We Desire

The ideal candidate for Sandia National Laboratories will in addition possess the following:

  • Experience developing software in one or more relevant languages, such as C, C++, Python, Rust, MATLAB, or similar languages used for embedded, scientific, or systems programming.
  • Familiarity with embedded software development, real-time systems, microcontrollers, system-on-chip platforms, digital signal processors, or other resource-constrained computing environments.
  • Exposure to FPGA development, hardware description languages, or high-level synthesis tools, such as VHDL, Verilog, System Verilog, HLS, Vivado, Quartus, or related tool chains.
  • Interest in deploying AI, machine learning, signal processing, or autonomy algorithms to edge, embedded, FPGA, or electronics platforms.
  • Familiarity with AI/ML frameworks, model optimization techniques, or edge-AI deployment concepts, such as PyTorch, Tensor Flow, ONNX, quantization, pruning, latency optimization, or hardware acceleration.
  • Experience using modern software engineering practices, including version control, unit testing, code reviews, continuous integration, debugging, documentation, and…
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