AI/ML Systems Engineer (2027 New College Graduate)

About the Role

GlobalFoundries is seeking an early-career AI/ML Systems Engineer to advance workload characterization and performance modeling across machine learning systems. The engineer will own quantitative analyses that connect workload behavior to hardware and software design decisions while communicating results across architecture, compiler, runtime, and product teams.

Key Responsibilities

• Characterize AI/ML workloads across inference and training, quantify compute and memory behavior, and identify bottlenecks using methods such as roofline analysis, operational intensity profiling, and bottleneck decomposition.
• Build and validate analytical or code-based models that estimate achievable throughput, latency, utilization, bandwidth consumption, and efficiency for real or projected hardware.
• Partner with hardware, compiler, and runtime engineers to translate workload findings into architectural and software optimization discussions, including memory subsystem sizing, scheduling, kernel optimization, and data layout tradeoffs.
• Own benchmarking or modeling efforts end to end, maintain clear and reproducible analysis artifacts, and communicate conclusions through written reports, presentations, and design reviews.
• Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety & Security requirements and programs.

Requirements & Tech Stack

• Education – Graduating with Bachelor’s or Master’s in Electrical Engineering, Computer Engineering, or related field from an accredited degree program.
• Must have at least an overall 3.0 GPA and proven good academic standing.
• Strong mathematical reasoning, including the ability to apply linear algebra, probability, and numerical analysis to performance estimation and numerical precision questions.
• Working understanding of computer architecture concepts, including cache hierarchies, memory bandwidth, and CPU pipeline fundamentals.
• Experience with Python and data analysis tooling such as NumPy, pandas, matplotlib, or similar.
• Exposure to machine learning frameworks such as PyTorch or TensorFlow.
• Language Fluency - English (Written & Verbal)
• Travel - Up to 10%

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; the ability to innovate and execute solutions that matter; the ability to navigate ambiguity.
• Strong written and verbal communication skills
• Strong planning & organizational skills
• Familiarity with the roofline model, FLOP counting, operator-level profiling, quantization analysis, or performance KPI frameworks.
• Exposure to compilation or intermediate representation concepts, including MLIR, IREE, TVM, or similar AI compiler infrastructure.