AI/ML Systems Engineer (2027 New College Graduate)

GlobalFoundries • Richardson, TX

3d

About The Position

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

The role involves characterizing AI/ML inference and training workloads; modeling achievable hardware throughput, latency, utilization, bandwidth consumption, and efficiency; and partnering with engineering teams on architectural and software optimization decisions. The engineer will own benchmarking or modeling efforts end to end, maintain clear and reproducible analysis artifacts, and present conclusions in reports, presentations, and design reviews.

This is a full-time opportunity for a 2027 new college graduate. The position requires travel up to 10%.

Requirements

• Graduating with a bachelor's or master's degree in Electrical Engineering, Computer Engineering, or a related field from an accredited degree program.
• Overall GPA of at least 3.0 and proven good academic standing.
• Strong mathematical reasoning, including applying linear algebra, probability, and numerical analysis to performance estimation and numerical precision questions.
• Working understanding of computer architecture, including cache hierarchies, memory bandwidth, and CPU pipeline fundamentals.
• Experience with Python and data analysis tools such as NumPy, pandas, matplotlib, or similar.
• Exposure to machine learning frameworks such as PyTorch or TensorFlow.
• English fluency, written and verbal.
• Ability to travel up to 10%.

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.
• 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.

Responsibilities

• Characterize AI/ML inference and training workloads, quantify compute and memory behavior, and identify bottlenecks using techniques such as roofline analysis, operational intensity profiling, and bottleneck decomposition.
• Build and validate analytical or code-based models to estimate throughput, latency, utilization, bandwidth consumption, and efficiency for real or projected hardware.
• Work 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 from start to finish and maintain clear, reproducible analysis artifacts.
• Communicate conclusions through written reports, presentations, and design reviews.
• Perform activities safely and responsibly and support Environmental, Health, Safety & Security requirements and programs.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level