Summer 2026 PhD Agent Task Planning Intern

Advanced Micro Devices, Inc•San Jose, CA

8h•Hybrid

About The Position

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. As an AMD intern, you’ll be placed at the epicenter of the AI ecosystem, working alongside experts and industry pioneers. You’ll do important work, learn new skills, expand your network, and gain real-world experience on projects that impact millions of end-users worldwide. Whether you’re an undergrad or a PhD student, your contributions matter—and your experience here will be a launchpad for what comes next. We are seeking a highly motivated co-op student to work on Agent Task Planning and Fine-Tuning for Resource-Constrained Client Devices. In this role: We will involve you in developing a task planning framework powered by Large Language Models, designed to operate effectively on client devices with limited resources. We will assign you the task of building and refining a focused prototype that demonstrates a practical use case, such as computer tasks, browser interactions, or database reasoning. Your responsibility will include extending the capabilities of constrained LLMs through context condensation, fine-tuning, and Low-Rank Adaptation (LoRA). We will train you to collaborate with AMD AI teams to help bring your developed techniques into practical, real-world deployments. You will gain experience in building efficient LLM systems, optimizing for edge environments, and contributing to scalable AI agent architectures. Note: By submitting your application, you are indicating your interest in AMD intern positions. We are recruiting for multiple positions, and if your experience aligns with any of our intern opportunities, a recruiter will contact you. #LI-DNI

Requirements

You are currently enrolled in a PhD program in Computer Science, Electrical Engineering, AI/ML, or a related field.
You have strong programming skills, preferably in Python, and experience building and testing AI prototypes.
You have worked with local AI inference, retrieval-augmented generation (RAG), fine-tuning, and LoRA techniques.
You are familiar with agent architectures involving memory, API connectors, workflow orchestration, and multi-component pipelines (MCP).
You have prior experience with AI agent task planning through coursework, research, or projects.

Nice To Haves

You have published or presented work at premier AI/ML conferences such as NeurIPS, ICML, or ICLR.

Responsibilities

Developing a task planning framework powered by Large Language Models, designed to operate effectively on client devices with limited resources.
Building and refining a focused prototype that demonstrates a practical use case, such as computer tasks, browser interactions, or database reasoning.
Extending the capabilities of constrained LLMs through context condensation, fine-tuning, and Low-Rank Adaptation (LoRA).
Collaborating with AMD AI teams to help bring your developed techniques into practical, real-world deployments.
Building efficient LLM systems, optimizing for edge environments, and contributing to scalable AI agent architectures.