Manufacturing AI Intern

An internship at onsemi offers a dynamic opportunity to gain hands-on experience through real-world projects that drive innovation in the semiconductor industry. Interns are entrusted with meaningful responsibilities and exposed to cutting-edge technologies, fostering both technical skill development and professional growth.

onsemi views internships as a strategic pipeline for entry-level career positions, providing a collaborative and inclusive environment where interns work alongside diverse teams and contribute to high-impact initiatives. The company’s commitment to sustainability, including its goal of achieving net-zero emissions by 2040, enables interns to engage in projects that align with global environmental priorities.

Key benefits include:

• Competitive compensation and medical benefits
• Flexible work hours aligned with academic schedules
• Access to Employee Resource Groups (ERGs) which foster a sense of belonging and provide opportunities for mentorship and community engagement
• Networking events, professional development workshops, and project showcases that build career readiness and visibility across the organization

Internship roles span multiple disciplines including engineering, business operations, data analytics, and finance, and are designed to align with onsemi’s strategic goals of innovation and workforce development. Structured programs such as rotational field sales and finance analyst tracks offer additional career pathways for interns transitioning into full-time roles.

· Pursuing or recently completed a BS or MS degree in Computer Science, Data Science, Software Engineering, Computer Engineering, Electrical Engineering, Industrial Engineering, or a related technical discipline.

· Strong programming, analytical, and problem-solving skills.

· Interest in artificial intelligence and emerging technologies.

· Strong written and verbal communication skills.

· Ability to work independently and collaborate within cross-functional teams.

Preferred Qualifications

· Personal, academic, or internship experience building an AI agent, chatbot, copilot, or automation solution.

· Experience using cloud platforms, preferably Microsoft Azure.

· Experience with Python data libraries such as Pandas, NumPy, or Scikit-Learn.

· Understanding of APIs, authentication, enterprise integrations, SQL, and data analytics.

· Exposure to semiconductor manufacturing, test, yield, quality, or operations analytics is a plus.

What You'll Gain?

· Hands-on experience applying AI to real-world semiconductor manufacturing challenges.

· Exposure to enterprise AI platforms, cloud infrastructure, and data ecosystems.

· Mentorship from engineers working on advanced AI, analytics, and manufacturing solutions.

· Experience developing production-oriented AI applications and intelligent agents.

· An opportunity to contribute to solutions that improve engineering efficiency, manufacturing insight, and yield performance.

The Yield Enhancement Systems (YES) team is seeking a motivated AI Engineering Intern to help develop next-generation AI solutions that improve manufacturing analytics, engineering productivity, and yield improvement across the semiconductor manufacturing lifecycle.

This role sits at the intersection of artificial intelligence, data engineering, manufacturing analytics, and software development. The intern will work with engineers, data scientists, and AI developers to build intelligent agents, curate engineering knowledge, develop data-driven workflows, and explore how Large Language Models (LLMs) can accelerate engineering decision-making.

Projects may include conversational AI, automated report generation, anomaly detection, yield analysis, document intelligence, and natural-language access to engineering and manufacturing data.

What You'll Do?

· Develop and evaluate AI agents that assist engineers with manufacturing, yield, and engineering analytics.

· Prototype intelligent workflows and engineering copilots using modern LLM platforms and agent frameworks.

· Build and maintain AI knowledge sources using engineering documentation, reports, training materials, and structured datasets.

· Design Retrieval-Augmented Generation (RAG) and semantic search solutions for engineering applications.

· Integrate AI applications with enterprise systems through APIs, databases, and agent tooling frameworks.

· Develop Python-based utilities for data preparation, automation, AI experimentation, and reporting.

· Create dashboards, reports, and visualizations that support yield monitoring and engineering investigations.

· Explore AI-assisted techniques for identifying trends, anomalies, yield excursions, and manufacturing issues.

· Collaborate with manufacturing, product, process, test, and software engineering teams to translate requirements into practical solutions.

· Use AI-assisted development tools to accelerate coding, testing, documentation, and troubleshooting.