Performance Engineering Intern in Poughkeepsie, NY

Performance Engineering Intern at IBM

At IBM, work is more than a job. We build, design, code, consult, invent, and collaborate to attempt things that were never thought possible. Are you ready to lead in this new era of technology and help solve some of the world's most challenging problems? If so, let's talk.

The IBM Z Performance and Architecture organization helps design and optimize the technologies behind IBM Z, IBM's flagship enterprise computing platform. IBM Z runs some of the world's most demanding business applications, processing massive transaction volumes while delivering high levels of reliability, security, and performance. IBM engineers the entire system stack, including processor architecture, hardware, firmware, operating systems, virtualization, middleware, applications, and performance tooling. This end-to-end ownership lets teams solve complex problems across the full computing stack for mission-critical enterprise workloads.

The team's work spans computer architecture, operating systems, performance engineering, data analytics, automation, workload analysis, and applied AI.

What You May Work On

• Analyzing real-world enterprise workloads at scale to understand system behavior and find performance opportunities using processor, memory, I/O, operating system, and application-level data
• Building and using models to evaluate processor and system performance
• Developing performance tests, benchmarks, tools, and automation
• Supporting computer architecture, performance tracing, modeling, and workload characterization
• Exploring AI and Generative AI to improve performance analysis and engineering productivity
• Collaborating with architects, hardware designers, software developers, and performance engineers

This role gives you a chance to apply classroom concepts to real-world enterprise systems and contribute to the development and performance of future IBM Z technologies.

Key Areas

• Computer Architecture and Processor Design
• Operating Systems and Systems Programming
• System Performance Engineering, Analysis, or Optimization
• Processor, Memory, and I/O Architecture
• Performance Modeling, Benchmarking, or Workload Analysis
• Probability and Statistics or Operations Research
• C/C++, Python, Assembly, or SystemVerilog
• Linux/Unix or RISC-V
• Multi-Core Systems or Digital Logic Design
• Data Analysis and Automation
• AI, Machine Learning, or Generative AI