$130,000–$160,000 Per Year
Algorithms, Analysis Skills, Artificial Intelligence (AI), Communication Skills, Computer Science, Computer Vision, Continuous Improvement, Cross-Functional, Data Analysis, Data Modeling, Data Sets, Deep Learning, Electrical Engineering, Machine Learning, Manufacturing, Manufacturing/Industrial Processes, Material Science, Metrology, Problem Solving Skills, Production Control, Production Systems, Python Programming/Scripting Language, SQL (Structured Query Language), Semiconductor Manufacturing, Semiconductors, Software Engineering, Team Player, Trend Analysis
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 Learning techniques to handle rare defect types.
- Knowledge of ML Ops tools (ML Flow, zen Flow etc.) for model deployment and monitoring in a production environment.
- Excellent communication skills to collaborate with cross-functional hardware and software teams.
Pay Range:
USD $130,000.00 - USD $160,000.00 /Yr.P
PDF Solutions
PDF Solutions, Inc. (NASDAQ: PDFS) is the leading provider of yield improvement technologies and services for the IC manufacturing process life cycle. PDF Solutions offers solutions that are designed to enable clients to lower costs of IC design and manufacture, enhance time to market, and improve profitability by addressing design and manufacturing interactions from product design to initial process ramps to mature manufacturing operations. PDF Solutions' Characterization Vehicle® (CV®) test chips provide the core modeling capabilities, and are used by more leading manufacturers than any other test chips in the industry. Exensio™, PDF Solutions' industry leading yield management and fault detection and classification enterprise software platform, enhances yield improvement and production control activities at leading fabs around the world. Headquartered in San Jose, Calif., PDF Solutions operates worldwide with additional offices in China, Europe, Japan, Korea and Taiwan. For the company's latest news and information, visit http://www.pdf.com/.