Company Overview
Group/Division
Job Description/Preferred Qualifications
Responsibilities:
The deep learning applications engineer will have the following responsibilities in the team:
- Develop and optimize deep learning models for image analysis, defect detection, and classification in semiconductor manufacturing.
- Collaborate with cross-functional teams including software engineers, hardware engineers, and domain experts to integrate AI solutions into inspection and metrology systems.
- Conduct research on state-of-the-art neural network architectures and apply them to real-world problems in wafer inspection and yield management.
- Implement scalable training pipelines and manage large datasets from semiconductor tools.
- Evaluate model performance and conduct rigorous testing to ensure robustness and accuracy in production environments.
- Contribute to publications, patents, and internal knowledge sharing.
Profile :
- Master’s or Ph.D. in Computer Science, Electrical Engineering, or related field with a focus on machine learning or computer vision.
- Experience with convolutional neural networks (CNNs), transformers, and other modern architectures.
- Knowledge of GPU computing and cloud-based AI model deployment.
- Familiarity with image processing, signal processing, and statistical analysis.
- You are dynamic and like to interact with people
- Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment
- Prior experience in the semiconductor industry or high-tech manufacturing is an advantage but not a must.
- Proficient in English with good communication skills
- This is a position based in Taiwan but may require regular travel to customers all over the world.
Minimum Qualifications
Master's Level Degree and 0 years related work experience;
Bachelor's Level Degree and related work experience of 2 years
We offer a competitive, family friendly total rewards package. We design our programs to reflect our commitment to an inclusive environment, while ensuring we provide benefits that meet the diverse needs of our employees.
KLA is proud to be an equal opportunity employer
Be aware of potentially fraudulent job postings or suspicious recruiting activity by persons that are currently posing as KLA employees. KLA never asks for any financial compensation to be considered for an interview, to become an employee, or for equipment. Further, KLA does not work with any recruiters or third parties who charge such fees either directly or on behalf of KLA. Please ensure that you have searched KLA’s Careers website for legitimate job postings. KLA follows a recruiting process that involves multiple interviews in person or on video conferencing with our hiring managers. If you are concerned that a communication, an interview, an offer of employment, or that an employee is not legitimate, please send an email to [email protected] to confirm the person you are communicating with is an employee. We take your privacy very seriously and confidentially handle your information.
Skills Required
- Master's or PhD in Computer Science, Electrical Engineering, or related field with focus on ML or computer vision
- Experience with convolutional neural networks (CNNs) and transformers
- Knowledge of GPU computing and cloud-based AI model deployment
- Familiarity with image processing, signal processing, and statistical analysis
- Experience implementing scalable training pipelines and managing large datasets
- Prior experience in the semiconductor industry or high-tech manufacturing
- Proficient in English with good communication skills
- Willingness to travel regularly to customers worldwide
KLA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about KLA and has not been reviewed or approved by KLA.
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Retirement Support — Retirement offerings include a 401(k) plan with company matching and financial planning support. Student debt assistance and related financial benefits reinforce long-term savings and security.
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Equity Value & Accessibility — Ownership programs include an Employee Stock Purchase Plan and broad-based RSU participation that extend equity beyond a narrow group. These elements complement competitive pay and bonuses to strengthen total rewards.
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Leave & Time Off Breadth — Time-off programs span paid time off, paid company holidays, and paid volunteer time. Family care and bonding leave and back-up care services add flexibility during life events.
KLA Insights
What We Do
KLA develops industry-leading equipment and services that enable innovation throughout the electronics industry. We provide advanced process control and process-enabling solutions for manufacturing wafers and reticles. In close collaboration with leading customers across the globe, our expert teams of physicists, engineers, data scientists and problem-solvers design solutions that move the world forward.
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