Applications Engineer (ML/Auto Defect Classification)

Benefits

Parental leave

Not verified

Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

Not verified

Verification

Not verified checked Jun 13, 2026

Salary

$130K-$160K From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

30% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Applications Engineer (ML/Auto Defect Classification) Milpitas, California Overview Role Summary We are seeking a Senior Applications Engineer to join our team, focusing on the development of cutting-edge machine learning and artificial intelligence solutions for the semiconductor industry. The ideal candidate will have extensive experience in creating robust and scalable software, with a strong background in data analysis, machine learning, and containerization technologies. Responsibilities Design and Implement ML/AI Algorithms: Help develop and implement advanced machine learning and AI-based algorithms for the automatic classification of defects in semiconductor inspection tools. Data Analysis: Analyze large volumes of defect data to identify critical patterns, trends, and anomalies, using this analysis to inform model development. Training and Model Development: Train, validate, and deploy defect classification models, ensuring they meet strict performance and accuracy requirements. System Optimization: Continuously improves the accuracy, efficiency, and reliability of the defect classification system through iterative development and optimization. Qualifications Education: Bachelor's or Master's degree in Computer Science, Electrical Engineering, Materials Science, or a related technical field. Machine Learning Expertise: Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch specifically for computer vision tasks (CNNs, Transformers). Semiconductor Knowledge: Familiarity with semiconductor manufacturing processes or inspection metrology is highly preferred. Data Proficiency: Experience handling large datasets and using tools like Pandas, NumPy and SQL for data preprocessing and feature engineering. Problem Solving: Strong analytical mindset with the ability to translate complex manufacturing defects into actionable data models, data ingestion, analysis, and visualization. Preferred Skills Experience with Mismatched Data or Active

Read the full description at careers-pdf.icims.com. FewerJobs shows a preview and links to the original posting.