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Copilot ML / Intelligent Automation Intern – NPI Process Automation Team
Austin, TX, United States
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On-site
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Internship
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Today
Who We Are
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.
What We Offer
Location:
Austin,TX, Santa Clara,CA
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. Visit our Careers website to learn more.
At Applied Materials, we care about the health and wellbeing of our employees. We’re 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. Learn more about our benefits.
Who We Are
Applied Materials is the 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 enables our customers to manufacture semiconductor chips and displays—the foundation of the devices we use every day. As the backbone of the global electronics industry, Applied Materials enables technologies that connect and transform our world, including AI, data‑driven automation, and intelligent systems.
Join Applied Materials to Make Possible® a Better Future.
What We Offer
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.
Role Summary
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.
Key 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.
Minimum Qualifications
- 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 (Num Py, 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
Preferred Qualifications
- Familiarity with large language models (LLMs), embeddings, or semantic search techniques
- Experience with ML frameworks such as Py Torch, Tensor Flow, 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)
Why This Internship Is Unique
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.
Additional Information Time Type:
Full time
Employee Type:
Intern / Student
Travel: Relocation Eligible:
Yes
The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. 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.
For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.
Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.
In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at Accommodations_Program@amat.com, or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.
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Applied Materialsについて

Applied Materials
PublicApplied Materials, Inc. is an American corporation that supplies equipment, services and software for the manufacture of semiconductor chips for electronics, flat panel displays for computers, smartphones, televisions, and solar products.
10,001+
従業員数
Santa Clara
本社所在地
$57B
企業価値
レビュー
3.5
10件のレビュー
ワークライフバランス
3.2
報酬
4.1
企業文化
3.8
キャリア
2.7
経営陣
2.5
65%
友人に勧める
良い点
Good compensation and benefits
Innovative and interesting projects
Supportive and talented colleagues
改善点
Limited career advancement opportunities
Poor management and lack of direction
High pressure and demanding environment
給与レンジ
43件のデータ
Junior/L3
L2
L3
L4
L5
L6
M3
M4
M5
M6
Senior/L5
Staff/L6
Junior/L3 · Data Scientist I
0件のレポート
$153,792
年収総額
基本給
-
ストック
-
ボーナス
-
$130,723
$176,861
面接体験
4件の面接
難易度
3.0
/ 5
期間
14-28週間
面接プロセス
1
Application Review
2
Recruiter Screen
3
Technical/Hiring Manager Interview
4
Final Round Interview
5
Offer
よくある質問
Technical Knowledge
Behavioral/STAR
Past Experience
Problem Solving
Culture Fit
ニュース&話題
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1d ago
Years of Rewards: $27 Bil From Applied Materials Stock - Trefis
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1d ago
Jim Cramer on Applied Materials: “It’s Not a Good Buy, It’s a Great Buy” - Yahoo Finance
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News
·
2d ago