AI Native Hardware & Software Codesign internship 2027

As an AI-Native Hardware-Software Co-design Research Intern, you will join a project aligned with your technical background and interests. Project areas may include AI-assisted compiler development, kernel generation and optimization, RTL generation, hardware verification, cross-layer hardware-software optimization, or reinforcement learning methods that extend open models to address challenging engineering problems. You are not expected to have experience across all these areas.

Working with a research mentor and an interdisciplinary team, you will:

• Contribute to research and prototype development in one or more project areas aligned with your expertise.
• Apply machine learning, generative AI, automated reasoning, reinforcement learning, or systems techniques to a well-defined hardware or software engineering challenge.
• Depending on the project, investigate reinforcement learning and related post-training methods for extending the capabilities of open models on complex tasks such as RTL generation, optimization, and verification.
• Design experiments and benchmarks to evaluate correctness, performance, efficiency, engineering productivity, or development-cycle improvements.
• Explore connections between your assigned area and adjacent layers of the computing stack.
• Collaborate with researchers and engineers across AI, compilers, computer architecture, digital design, verification, and systems software.
• Document your methods and findings and communicate results through technical presentations, reports, code, and potential research publications.

Projects may involve the IBM Spyre accelerator software stack and IBM Systems, including IBM Z and IBM Power, while also exploring methods applicable to future processors, accelerators, and computing platforms.