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AI​/ML Systems Engineering Intern; Summer

Job in Richardson, Dallas County, Texas, 75080, USA
Listing for: GlobalFoundries inc.
Full Time, Seasonal/Temporary, Apprenticeship/Internship position
Listed on 2026-10-22
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 20 - 40 USD Hourly USD 20.00 40.00 HOUR
Job Description & How to Apply Below
About Global Foundries Global Foundries  (GF) is a leading manufacturer of essential semiconductors, enabling AI at scale from the cloud to the physical world. Through deep partnerships with customers, GF delivers differentiated, power efficient and high performance solutions for high growth markets. GF is a trusted and holistic technology partner for customers around the world. GF’s talented, global team remains focused every day on security, longevity, and sustainability.

For more information, visit  Program Overview:

Our Interns & Co-ops are our entry-level talent pipeline for GF across the globe. Our goal is to provide students with a meaningful work experience that will equip them with the skills to embark on a career in the fast-paced and growing semiconductor industry after graduation. As an intern at GF, you’ll experience one-on-one mentorship, work assignments that prioritize your growth and potential, professional development opportunities, and the chance to network with executives.

Summary of Role:

Global Foundries is seeking a curious and motivated AI/ML Systems Engineering Intern to characterize machine learning workloads and analyze how their compute and memory demands map to hardware resources. Working with experienced hardware and software engineers, the intern will build practical skills in performance experimentation, analytical modeling, and clear technical communication.

Essential

Responsibilities include:

Run and interpret performance experiments for AI/ML workloads, including classical inference pipelines and modern model architectures, and document observations using reproducible analysis methods.

Build analytical models to estimate throughput, latency, utilization, operational intensity, and memory bandwidth requirements, and identify likely compute or memory bottlenecks.

Collaborate with hardware and software engineers to connect workload behavior with architectural and implementation decisions, including cache, memory subsystem, runtime, and compiler considerations.

Present findings through concise reports, visualizations, and technical discussions, and grow toward independent ownership of a defined workload characterization study during the internship.

Other Responsibilities:

Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety & Security requirements and programs.

Required Qualifications:

Education – At least a sophomore at time of application and actively pursuing a Bachelor’s or Master’s in Electrical Engineering, Computer Engineering, or related field through an accredited degree program during the time of internship.

Must have at least an overall 3.0 GPA and be in good academic standing.

Coursework or project experience applying linear algebra, probability, numerical analysis, or related mathematical methods to engineering or computing problems.

Working understanding of computer architecture concepts such as cache hierarchies, memory bandwidth, and CPU pipeline fundamentals.

Experience using Python and data analysis tools such as Num Py, pandas, matplotlib, or similar.

Language Fluency
- English (Written & Verbal)
Travel
- Up to 10%
Ability to work at least 40 hours per week during the internship.

Preferred Qualifications:

Prior related internship or co-op experience

Demonstrated prior leadership experience in the workplace, school projects, competitions, etc.

Strong interest in leveraging AI tools and emerging technologies to enhance productivity, streamline workflows, and support effective decision-making.

Project management skills, i.e., the ability to innovate and execute on solutions that matter; the ability to navigate ambiguity.

Strong written and verbal communication skills

Strong planning & organizational skills

Exposure to…
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