AI/ML Systems Engineer Intern: Performance & Hardware

GlobalFoundries; Richardson (TX); Sur place; USD 28 000 - 55 000; Plein temps

Résumé du poste

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. You’ll gain hands-on experience with performance experimentation, analytical modeling, and clear technical communication.

You will work with experienced hardware and software engineers to connect workload behavior with architectural decisions, and you’ll present findings through reports and

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 NumPy, 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.

Responsabilités

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

Connaissances

Linear algebra

Probability

Numerical analysis

Computer architecture concepts

English (Written & Verbal)

Formation

Bachelor's or Master’s in Electrical Engineering, Computer Engineering, or related field

Outils

Python

NumPy

pandas

matplotlib

Description du poste

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. You’ll gain hands-on experience with performance experimentation, analytical modeling, and clear technical communication.

You will work with experienced hardware and software engineers to connect workload behavior with architectural decisions, and you’ll present findings through reports and