AI/ML Systems Engineer (2027 New College Graduate)

Job Title

AI/ML Systems Engineer (2027 New College Graduate)

Role Summary

Early-career engineering role responsible for workload characterization and performance modeling for machine learning systems. The engineer will quantify compute and memory behavior, build performance models, and translate findings into hardware and software design recommendations.

The role works closely with architecture, compiler, runtime, and product teams to inform memory subsystem sizing, scheduling, kernel optimization, and data-layout tradeoffs.

Experience Level

Entry-level - new college graduate. This position is part of a new graduate hiring program; prior internship experience is helpful but not required.

Responsibilities

Primary responsibilities focus on quantitative analysis, modeling, and communication of ML workload behavior.

• Characterize AI/ML workloads for inference and training; identify bottlenecks using roofline analysis, operational intensity profiling, and bottleneck decomposition.
• Develop and validate analytical or code-based models to estimate throughput, latency, utilization, bandwidth consumption, and efficiency for current or projected hardware.
• Partner with hardware, compiler, and runtime engineers to translate workload findings into optimization opportunities and architectural tradeoffs.
• Own benchmarking and modeling efforts end-to-end; maintain clear, reproducible analysis artifacts and document conclusions in reports and presentations.
• Communicate results in design reviews and cross-functional discussions.
• Perform work in accordance with Environmental, Health, Safety & Security requirements.

Requirements

Must-have technical skills and core qualifications are listed first; preferred or nice-to-have items follow.

• Must-have: Strong mathematical reasoning; ability to apply linear algebra, probability, and numerical analysis to performance estimation and precision questions.
• Working understanding of computer architecture concepts, including cache hierarchies, memory bandwidth, and CPU pipeline fundamentals.
• Proficiency with Python and data-analysis tooling such as NumPy, pandas, and matplotlib.
• Exposure to machine learning frameworks such as PyTorch or TensorFlow.
• English fluency (written and verbal).
• Willingness to travel up to 10%.
• Nice-to-have: Prior internship or co-op experience; familiarity with roofline model, FLOP counting, operator-level profiling, quantization analysis, or performance KPI frameworks.
• Exposure to compilation or intermediate representation concepts (MLIR, IREE, TVM, or similar AI compiler infrastructure).
• Project management, leadership on projects, and strong written/verbal communication skills.

Education Requirements

Graduating with a Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or a related field from an accredited program. Minimum overall GPA of 3.0 and demonstrated good academic standing.

About the Company

Company: GlobalFoundries

Headquarters: Saratoga Springs, New York, USA

GlobalFoundries is a leading contract manufacturer for the global semiconductor industry, with facilities in multiple countries, including the USA. The company develops a broad portfolio of semiconductor technologies and employs around 13,000 people worldwide. GlobalFoundries focuses on enhancing competitiveness in specialized application solutions and fostering innovation in mobile communications, consumer electronics, and automotive applications.