Senior Vision Systems Engineer for AI-Driven Semiconductor Imaging

Lam Research; Tualatin (OR); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

On-site Flex

Virtual Flex

Job summary

Lam Research in Portland area is seeking a Vision System Data Science Engineer to lead design, development, and deployment of advanced computer vision and ML solutions for complex industrial applications.

You will transform image and sensor data into actionable insights, partnering with customers and internal teams to improve product quality, process control, and efficiency. Strong leadership and production-grade deployment experience are essential.

Qualifications

• Master's degree with 8+ years in data science, computer science, physics, or related field.
• PhD with 5+ years of relevant experience is acceptable.

Responsibilities

• Design, develop, and deploy computer vision algorithms for industrial applications.
• Build scalable ML/DL models using image, video, and sensor data.
• Lead data science lifecycle: collection, labeling, training, deployment, monitoring.
• Develop image-processing pipelines with modern CV frameworks and cloud tech.
• Define data quality standards and metrics for production readiness.
• Collaborate with engineers and product teams to deliver integrated vision solutions.
• Conduct root-cause analysis and use analytics to improve yield and equipment performance.
• Evaluate emerging AI/ML technologies to drive innovation.
• Mentor junior engineers on best practices in data science and ML.

Skills

Computer Vision

Machine Learning

Deep Learning

C/C++

Python

OpenCV

Cloud platforms

MLOps

Education

Master's degree in Data Science/CS/Physics

PhD with 5+ years experience

Tools

TensorFlow

PyTorch

OpenCV

Job description

Lam Research in Portland area is seeking a Vision System Data Science Engineer to lead design, development, and deployment of advanced computer vision and ML solutions for complex industrial applications.

You will transform image and sensor data into actionable insights, partnering with customers and internal teams to improve product quality, process control, and efficiency. Strong leadership and production-grade deployment experience are essential.