Summer 2027 ASIC Design Co-Op/ Intern

About the Role

We are seeking a highly motivated AI Agentic Flow for GPU ASIC Design Intern/Co-op to join our team. In this role, you will help develop and apply AI-driven agentic workflows that improve the efficiency, quality, and automation of GPU ASIC design and verification processes. This role requires the student to work full time onsite throughout the duration of the co-op/intern term.

• Location: Orlando, Florida
• Duration: May 24, 2027 or June 21, 2027

Key Responsibilities

• Develop AI agents that assist engineers with GPU ASIC design activities, including specification analysis, RTL development, verification planning, debug, and documentation generation.
• Work with design, verification, and architecture teams to identify engineering workflows that can be enhanced through large language models (LLMs), retrieval systems, and autonomous AI agents.
• Build, evaluate, and optimize agentic workflows that leverage engineering data sources such as design specifications, code repositories, simulation results, and technical documentation.
• Measure AI agent effectiveness, analyze workflow improvements, and help create scalable solutions that improve engineering productivity and design quality.

What You Will Learn

• Gain hands-on experience applying AI and agentic systems to complex semiconductor engineering challenges.
• Learn modern GPU ASIC design and verification workflows.
• Develop practical experience with large language models, AI agent frameworks, retrieval-augmented generation (RAG), automation pipelines, and engineering productivity tools.
• Work alongside experienced GPU architects, design engineers, verification engineers, and AI researchers on real-world engineering problems.

Requirements & Tech Stack

• Currently pursuing a Bachelor's, Master's, or Ph.D. degree in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Data Science, or a related technical field, with at least one year of coursework remaining after the internship/co-op.
• 3rd year, 4th year, or graduate-level studies with coursework in computer architecture, digital design, machine learning, artificial intelligence, or software engineering.
• Experience programming in Python and familiarity with software development practices, data structures, and algorithm design.
• Understanding of machine learning concepts, large language models, agentic AI systems, or AI application development.
• Familiarity with Linux environments, scripting, data analysis, or automation tools.
• Exposure to digital logic design, computer architecture, RTL development, hardware verification, or semiconductor design concepts.

Preferred Qualifications

• Experience building AI applications using LLMs, prompt engineering, RAG systems, vector databases, MCPs, or agent frameworks.
• Experience with Verilog, SystemVerilog, RTL design, simulation, verification, or hardware development projects.
• Knowledge of GPU architecture, parallel computing, hardware acceleration, or AI accelerator design.
• Experience analyzing large datasets, creating engineering automation solutions, or developing workflow orchestration tools.
• Participation in research projects, hackathons, open-source initiatives, or academic projects involving AI, semiconductor design, or hardware/software co-design.