Overview:
At PDF Solutions, we are at the forefront of revolutionizing the semiconductor industry. Our cutting-edge technologies and data-driven solutions empower semiconductor manufacturers to achieve unprecedented levels of efficiency, quality, and innovation. By joining our team, you’ll have the opportunity to work with some of the brightest minds in the industry, tackle complex challenges, and contribute to groundbreaking advancements that shape the future of technology. Headquartered in Santa Clara, California, PDF Solutions also operates worldwide in Canada, China, France, Germany, Italy, Japan, Korea, and Taiwan.
We are seeking a Senior Software Developer 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: 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.
• Model Development: Train, validate, and deploy defect classification models, ensuring they meet strict performance and accuracy requirements.
• System Optimization: Continuously improve the accuracy, efficiency, and reliability of the defect classification system through iterative development and optimization.

Qualifications:

• Design and Implement ML/AI Algorithms: 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.
• Model Development: Train, validate, and deploy defect classification models, ensuring they meet strict performance and accuracy requirements.
• System Optimization: Continuously improve the accuracy, efficiency, and reliability of the defect classification system through iterative development and optimization