Intern, R&D Graduate Year-Round - Counter-Autonomy & Intrusion Detection, Hybrid

Intern, R&D Graduate Year‑Round - Counter‑Autonomy & Intrusion Detection, Hybrid

We are seeking R&D focused graduate student interns for a year‑round position in our Counter‑Autonomy and Intrusion Detection department. You will assist with a broad range of national security challenges associated with the physical security of nuclear materials, critical infrastructure and national security sites. Daily activities will involve working with staff members and technologists on multiple projects typically centered around three main bodies of work: autonomy and unmanned systems, algorithm development and code generation, and R&D for novel physical intrusion (people, drones, vehicles) detection methods.

The successful candidate must be willing to learn a variety of topics from multiple domains, such as physical security, computer science, computer engineering, sensors and sensor theory, machine learning, optical science, robotics/mechatronics, and signal processing. Interns will work in a collaborative, mentored research environment with opportunities to learn experimental methods, software development practices, and technical communication.

On any given day, specific project areas may include:

• Assisting existing project teams to develop, integrate, test, and evaluate counter‑autonomy technologies
• Supporting software development for data processing, analysis, visualization, and algorithm evaluation
• Assisting with the collection, organization, labeling, and analysis of experimental or simulated data
• Developing and evaluating machine learning or signal‑processing methods for detection, classification, tracking, or characterization tasks
• Supporting hardware/software integration for sensors, embedded devices, data acquisition systems, or prototype platforms
• Participating in laboratory, simulation, or field‑test activities to evaluate emerging concepts and prototype capabilities
• Developing tools to support experiment planning, performance assessment, and technical decision‑making
• Working with multidisciplinary teams across software engineering, electrical engineering, mechanical engineering, data science, and systems engineering
• Documenting technical work and communicating results through presentations, reports, and team discussions

This position offers the opportunity to contribute to challenging national security problems while gaining experience in applied research, experimental systems, data analysis, machine learning, and integrated technology development.

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.

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 (https://(Use the "Apply for this Job" box below).).

• 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 maintain a U.S. security clearance which requires U.S. citizenship

• Experience with Python for scientific computing, automation, data processing, or algorithm development
• Familiarity with Python libraries such as Num Py, Sci Py, pandas, matplotlib, scikit‑learn, OpenCV, or similar tools
• Familiarity with PyTorch, Tensor Flow, or related machine learning frameworks
• Experience or coursework in machine learning, deep learning, computer vision, signal processing, or data analytics
• Experience collecting, processing, labeling, visualizing, or analyzing experimental data
• Experience with hardware/software integration, embedded systems, sensors, or data acquisition systems
• Intere…