AI-Driven Bill of Materials (BOM) Generation and Management Intern

Intern (AI-Driven Bill of Materials (BOM) Generation and Management) — Product Data Management (PDM)

At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future. Join us and, together, we’ll advance your career.

As an AMD [intern/co-op], 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.

Location, Criteria, and Duration

• Location: Singapore
• Criteria: Current students studying in Universities based in Singapore
• Internship duration: Begins 4 Jan 2027 and ends 28 May 2027. Optional extension concludes on 6 Aug 2027.

What You Can Expect to Learn

As a Product Data Management (PDM) Intern, you will gain hands-on experience in developing AI-driven solutions to automate Bill of Materials (BOM) management for AMD’s MPU and GPU product lines. You will work with real-world semiconductor product data supporting Server, Client, Desktop, Embedded, Gaming, and Data Center products to improve data quality, operational efficiency, and product release readiness.

Throughout the internship, you will collaborate with cross-functional teams—including Product Engineering, Design, Packaging, Test, Supply Chain, Procurement, Finance, and Business Unit—to apply AI in enhancing engineering workflows and business operations. Opportunities include:

• Developing AI-powered automation solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and Robotic Process Automation (RPA)
• Gaining practical experience in PDM, Master Data governance, and intelligent process automation
• Building and deploying AI applications that improve BOM creation, validation, and lifecycle management
• Receiving mentorship from experienced technical leaders in AI, data science, automation, and semiconductor product lifecycle management

Project Overview

The project focuses on designing and developing a unified AI platform that combines Enterprise Knowledge Management, Business Intelligence, and automated BOM Execution. The platform will provide conversational AI capabilities in creating, validating, maintaining, and releasing BOMs for AMD’s complex MPU/GPU products.

Key Responsibilities

• Develop AI-driven solutions to automate repetitive engineering tasks associated with BOM creation, validation, and release to improve product data quality while reducing manual effort and release cycle times.
• Collaborate with cross-functional stakeholders from multiple product lines to implement intelligent BOM automation solutions.
• Design and develop an Internal Copilot PDM agent, integrating Product Lifecycle Management (PLM) requests, BOM reporting, data dictionary, PDM dashboards, and Confluence documentation.
• Support BOM creation and release activities in production/engineering life cycles for AMD’s MPU and GPU product portfolios.

Who Are We Looking For

We are seeking highly self-driven students passionate about Artificial Intelligence, data engineering, and process automation. The ideal candidate should have strong analytical and problem-solving skills for applying AI to solve real-world engineering challenges, and programming skills—particularly in Python/SQL and data processing.

You should be proactive, capable of learning new technologies quickly, and able to collaborate effectively with cross-functional teams. Experience with AI, machine learning, LLMs, or automation projects is highly desirable.

Relevant Skillsets

• Programming Languages: Python, SQL, Java, C/C++
• AI/Data Science Skills: Machine Learning, LLMs, Retrieval-Augmented Generation (RAG), Prompt Engineering, Generative AI, Data Cleaning, Predictive Analytics, NLP, Deep Learning, AI Agents
• AI Frameworks & Tools: OpenAI API, Azure AI Services, Microsoft Copilot, Power BI, Streamlit, Git, RPA
• Data & Enterprise Systems: Added advantage—experience with PLM systems, Enterprise Resource Planning (ERP) systems, structured and unstructured data, SQL cloud databases, REST APIs, and data visualization/reporting platforms

Academic Credentials

• Candidates pursuing a bachelor’s or master’s degree in data science or computer science