Performance Engineering Intern: Enterprise Systems & AI

Monmouth University; City of Poughkeepsie (NY); On-site; USD 28,000 - 41,000; Part time

Job summary

IBM in Poughkeepsie seeks a Performance Engineering Intern to help analyze enterprise workloads, build performance models, and develop tests and automation across the full IBM Z stack. You will collaborate with architects, hardware designers, and software engineers to drive performance improvements on world‑class enterprise systems.

The role provides hands-on experience with performance tracing, workload characterization, and AI-assisted analysis, applying classroom concepts to real-world IBM Z

Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
• Fundamental understanding of computer architecture, operating systems, software development, or digital systems.
• Programming experience in C, C++, Python, Java, or Assembly.
• Strong analytical and problem-solving skills.
• Strong communication and teamwork skills.

Responsibilities

• Analyze real-world enterprise workloads at scale to understand system behavior and uncover performance opportunities.
• Build and use models to evaluate processor and system performance.
• Develop performance tests, benchmarks, tools, and automation.
• Support computer architecture, performance tracing, modeling, and workload characterization.
• Explore AI and Generative AI to improve performance analysis and engineering productivity.
• Collaborate with architects, hardware designers, software developers, and performance engineers.

Skills

Programming languages

Analytical thinking

Communication

Teamwork

Education

High School Diploma/GED

Bachelor’s/Master’s in CS/CE/EE

Job description

IBM in Poughkeepsie seeks a Performance Engineering Intern to help analyze enterprise workloads, build performance models, and develop tests and automation across the full IBM Z stack. You will collaborate with architects, hardware designers, and software engineers to drive performance improvements on world‑class enterprise systems.

The role provides hands-on experience with performance tracing, workload characterization, and AI-assisted analysis, applying classroom concepts to real-world IBM Z