AI/ML Systems Engineering Intern (Summer 2027)

GlobalFoundries • Richardson, TX

3d

About The Position

GlobalFoundries 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 develop practical skills in performance experimentation, analytical modeling, and technical communication. The internship offers one-on-one mentorship, growth-focused work assignments, professional development opportunities, and networking with executives. The intern is expected to grow toward independently owning a defined workload characterization study during the internship. Applicants must be at least a sophomore when applying and actively pursuing a relevant bachelor's or master's degree during the internship. The role requires availability to work at least 40 hours per week and may involve up to 10% travel.

Requirements

• At least sophomore standing at the time of application and active enrollment during the internship in an accredited bachelor's or master's program in Electrical Engineering, Computer Engineering, or a related field.
• Overall GPA of at least 3.0 and 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, including cache hierarchies, memory bandwidth, and CPU pipeline fundamentals.
• Experience using Python and data analysis tools such as NumPy, pandas, matplotlib, or similar.
• English fluency, both written and verbal.
• Ability to work at least 40 hours per week during the internship.

Nice To Haves

• Prior related internship or co-op experience.
• Demonstrated leadership experience in the workplace, school projects, competitions, or similar settings.
• Interest in using AI tools and emerging technologies to enhance productivity, streamline workflows, and support effective decision-making.
• Project management skills, including the ability to innovate, execute solutions, and navigate ambiguity.
• Strong written and verbal communication skills.
• Strong planning and organizational skills.
• Exposure to PyTorch or TensorFlow and concepts such as FLOP counting, operator-level profiling, or the roofline model.
• Exposure to compilation, intermediate representations, or AI compiler toolchains such as MLIR, IREE, TVM, or similar.

Responsibilities

• 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 develop toward independent ownership of a workload characterization study.
• Perform all activities safely and responsibly and support Environmental, Health, Safety & Security requirements and programs.

Benefits

• One-on-one mentorship
• Professional development opportunities
• Opportunity to network with executives

What This Job Offers

• Career Level: Intern