Senior Applications Support Engineer

Overview

At PDF Solutions , we help the world's leading semiconductor manufacturers improve yield, quality, reliability, and operational efficiency through advanced analytics, machine learning, and engineering solutions. We are looking for an Senior Applications Support Engineer to support next-generation semiconductor inspection and analytics products, working at the intersection of software, machine learning, data engineering, and customer success.

Responsibilities

Provide technical support for semiconductor inspection and analytics applications.

Train, validate, and deploy ML/AI-based defect classification models while ensuring high accuracy and performance.

Support deployment, validation, and optimization of ML/AI-based defect classification solutions.

Analyze large volumes of defect data to identify patterns, trends, and anomalies that drive product and model improvements.

Deploy and maintain containerized applications using Docker and Kubernetes.

Collaborate with engineering, product, and customer teams to ensure successful solution deployment and adoption.

Qualifications

✅ Master's / PhD degree in Computer Science, Electrical Engineering, Data Science, Materials Science, or a related technical field.

✅ 6+ years of experience supporting enterprise software, analytics applications, or manufacturing systems.

✅ 6+ years of hands-on Python development experience.

✅ Experience with:

OpenCV, Pandas, NumPy, SciPy, and Scikit-learn

Machine learning frameworks such as PyTorch or TensorFlow

Computer vision, image analysis, or defect classification applications

MLOps and production ML deployments

Kafka, InfluxDB, or similar data platforms

Docker and Kubernetes

✅ Strong problem-solving, troubleshooting, and root-cause analysis skills.

✅ Excellent verbal and written communication skills with the ability to work directly with customers and cross-functional teams.

Why Join PDF Solutions?

Work on cutting-edge AI/ML applications for semiconductor manufacturing.

Collaborate with industry-leading engineers and customers.

Gain experience with advanced analytics, distributed computing, and machine learning technologies.

Make a direct impact on next-generation manufacturing solutions used across the semiconductor industry.

Pay Range

USD $130,000.00 - USD $180,000.00 /Yr.

Provide technical support for semiconductor inspection and analytics applications.

Train, validate, and deploy ML/AI-based defect classification models while ensuring high accuracy and performance.

Support deployment, validation, and optimization of ML/AI-based defect classification solutions.

Analyze large volumes of defect data to identify patterns, trends, and anomalies that drive product and model improvements.

Deploy and maintain containerized applications using Docker and Kubernetes.

Collaborate with engineering, product, and customer teams to ensure successful solution deployment and adoption.

✅ Master's / PhD degree in Computer Science, Electrical Engineering, Data Science, Materials Science, or a related technical field.

✅ 6+ years of experience supporting enterprise software, analytics applications, or manufacturing systems.

✅ 6+ years of hands-on Python development experience.

✅ Experience with:

OpenCV, Pandas, NumPy, SciPy, and Scikit-learn

Machine learning frameworks such as PyTorch or TensorFlow

Computer vision, image analysis, or defect classification applications

MLOps and production ML deployments

Kafka, InfluxDB, or similar data platforms

Docker and Kubernetes

✅ Strong problem-solving, troubleshooting, and root-cause analysis skills.

✅ Excellent verbal and written communication skills with the ability to work directly with customers and cross-functional teams.

Why Join PDF Solutions?

Work on cutting-edge AI/ML applications for semiconductor manufacturing.

Collaborate with industry-leading engineers and customers.

Gain experience with advanced analytics, distributed computing, and machine learning technologies.

Make a direct impact on next-generation manufacturing solutions used across the semiconductor industry.