Copilot ML / Intelligent Automation Intern – NPI Process Automation Team

Applied Materials • Austin, TX

1d • Onsite

About The Position

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world. At Applied Materials, we value learning, collaboration, and practical innovation. As a summer intern, you will work alongside senior engineers, program leaders, and domain experts on real production problems, not toy examples. You will gain hands‑on experience applying machine learning and AI copilots to complex engineering and manufacturing workflows, receive mentorship on system‑level thinking, and see how AI solutions are operationalized at scale in a global manufacturing environment. This internship provides hands‑on experience in developing and prototyping Copilot‑based ML and Intelligent Automation (IL) solutions to improve the efficiency and quality of New Product Introduction (NPI) processes. The intern will focus on using ML, LLMs, and information‑retrieval techniques to: speed execution of NPI workflows, improve accuracy and first‑time‑right outcomes, and enhance recall and reuse of lessons learned, BKMs, and historical data. The role sits at the intersection of AI/ML, process automation, and manufacturing engineering, with direct exposure to real-world constraints such as cycle time, repeat errors, and data quality. Unlike generic AI internships, this role focuses on applying AI where correctness and repeatability matter, not just model accuracy. You’ll work on problems where improved recall of lessons learned or a better decision recommendation can prevent real manufacturing issues and materially improve execution outcomes.

Requirements

• Currently pursuing a Bachelor’s, Master’s, or Ph.D. degree in Computer Science, Data Science, Electrical Engineering, Industrial Engineering, or a related field
• Coursework or project experience in machine learning, AI, data science, or information retrieval
• Programming experience in Python (required); familiarity with data analysis libraries (NumPy, pandas, scikit‑learn)
• Strong analytical thinking and ability to translate open‑ended problems into implementable solutions
• Effective written and verbal communication skills
• Ability to work in a collaborative, cross‑functional engineering environment

Nice To Haves

• Familiarity with large language models (LLMs), embeddings, or semantic search techniques
• Experience with ML frameworks such as PyTorch, TensorFlow, or similar
• Exposure to workflow automation, copilots, or RPA concepts
• Interest in manufacturing, NPI, or complex engineering systems
• Familiarity with AI‑assisted coding tools (e.g., GitHub Copilot or similar)

Responsibilities

• Assist in the design and prototyping of Copilot / LLM‑enabled workflows for NPI process automation (e.g., issue analysis, repeat detection, decision support).
• Explore and implement machine learning and information‑retrieval approaches (semantic search, embeddings, similarity detection) to improve reuse of lessons learned and historical engineering knowledge.
• Support data preparation, labeling, and analysis across structured and unstructured sources (documents, BKMs, process logs, issue records).
• Develop proof‑of‑concept solutions that demonstrate improvements in execution speed, accuracy, or recall quality for real NPI use cases.
• Collaborate closely with NPI engineers, manufacturing teams, and software partners to understand workflows and validate solutions.
• Evaluate solution performance and document findings, tradeoffs, and limitations for potential production adoption.

Benefits

• You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers.
• We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company.
• Applied Materials cares about the health and wellbeing of its employees and is committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go.
• In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Number of Employees: 11-50 employees