Among computer and information research scientists, AI is already used for a large share of the tasks. Measured exposure for computer and information research scientists: 34% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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About the job

About GlobalFoundries

GlobalFoundries (GF) is a leading manufacturer of essential semiconductors, enabling AI at scale from the cloud to the physical world. Through deep partnerships with customers, GF delivers differentiated, powerefficient and highperformance solutions for highgrowth markets. GF is a trusted and holistic technology partner for customers around the world. GF’s talented, global team remains focused every day on security, longevity, and sustainability. For more information, visit www.gf.com.

New College Graduates Overview:

We offer many full-time employment paths for recent graduates, which provide accelerated training in a fast-paced work environment, cross-functional working opportunities, and talent mobility. New college graduates are provided with mentorship, networking, and leadership opportunities, which give our new team members life-long connections and skills.

Summary of 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.

Essential Responsibilities include:

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.

Other Responsibilities:

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

Required Qualifications:

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, i.e. 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.

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Expected Salary Range $86,000.00 - $148,000.00

The exact Salary will be determined based on qualifications, experience and location.

If you need a reasonable accommodation for any part of the employment process, please contact us by email at usaccommodations@gf.com and let us know the nature of your request and your contact information. Requests for accommodation will be considered on a case-by-case basis. Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address.

An offer with GlobalFoundries is conditioned upon the successful completion of pre-employment conditions, as applicable, and subject to applicable laws and regulations.

GlobalFoundries is fully committed to equal opportunity in the workplace and believes that cultural diversity within the company enhances its business potential. GlobalFoundries goal of excellence in business necessitates the attraction and retention of highly qualified people. Artificial barriers and stereotypic biases detract from this objective and may be illegally discriminatory.

All policies and processes which pertain to employees including recruitment, selection, training, utilization, promotion, compensation, benefits, extracurricular programs, and termination are created and implemented without regard to age, ethnicity, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, sexual orientation, gender identity or expression, veteran status, or any other characteristic or category specified by local, state or federal law