Vision System Engr 4

Lam Research

Tualatin, OR, United States11h ago

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Key details

Location: Tualatin, OR, United States
Work style: Onsite
Level: Senior
Experience: 8–11 yrs
Function: other
Focus area: other
Posted: 11h ago

Skills

ai/mlalgorithmsanomaly detectionawsazurebig datac++cloud computingcomputer visiondata qualitydata sciencedatabricksdeep learningdistributed computinggcpimage processingindustrial automationmachine learningmlopsopencvprocess controlpythonpytorchroboticsroot cause analysissparksqlstatistical modelingtensorflow

About the role

The group you’ll be a part of

In the Global Products Group, we are dedicated to excellence in the design and engineering of Lam's etch and deposition products. We drive innovation to ensure our cutting-edge solutions are helping to solve the biggest challenges in the semiconductor industry.

The impact you’ll make

Join Lam as a Data Scientist, where you'll design, develop, and program methods to analyze unstructured and diverse big data into actionable insights. You'll develop algorithms and automated processes to evaluate large data sets from disparate sources. Your expertise in generating, interpreting, and communicating actionable insights enables Lam to make informed and data-driven decisions.

What you’ll do

Position Summary

We are seeking a highly skilled Vision System Data Science Engineer (Level 4) to lead the design, development, and deployment of advanced computer vision and machine learning solutions for complex industrial and manufacturing applications. The ideal candidate combines deep expertise in data science, computer vision, machine learning, and software engineering to transform image and sensor data into actionable insights that improve product quality, process control, and operational efficiency. As a senior technical contributor, you will drive end-to-end vision system development, collaborate with cross-functional teams, and provide technical leadership in AI-driven imaging and analytics initiatives.

Key Responsibilities

Design, develop, and deploy computer vision algorithms for detection, classification, segmentation, anomaly detection, and predictive analytics.

Build scalable machine learning and deep learning models using image, video, and multimodal sensor data.

Lead the complete data science lifecycle, including data collection, labeling, feature engineering, model training, validation, deployment, and monitoring.

Develop robust image-processing pipelines utilizing modern computer vision frameworks and cloud technologies.

Define data quality standards and establish model performance metrics to ensure production readiness.

Collaborate with process engineers, software developers, hardware engineers, and product teams to deliver integrated vision solutions.

Conduct root-cause analysis and use advanced analytics to improve yield, process stability, and equipment performance.

Drive innovation by evaluating emerging AI, machine learning, and computer vision technologies.

Mentor junior engineers and provide technical guidance on best practices in data science and machine learning.

Present technical findings, project updates, and recommendations to engineering leadership and business stakeholders.

Who we’re looking for

Master's degree in Data Science, Computer Science, Physics, or related field with 8+ years of relevant experience; or Ph.D. with 5+ years of experience.

Strong expertise in:
- Computer Vision
- Machine Learning and Deep Learning
- Statistical Modeling and Experimental Design
- Image Processing and Pattern Recognition

Proficiency C/C++ , in Python and scientific computing libraries such as:
- TensorFlow and/or PyTorch
- OpenCV

Experience developing and deploying production AI/ML systems.

Strong knowledge of CNNs, Vision Transformers (ViTs), object detection, segmentation, and anomaly detection methodologies.

Experience with cloud platforms (Azure, AWS, or GCP) and MLOps practices.

Ability to handle large-scale structured and unstructured datasets.

Strong communication and stakeholder-management skills.

Preferred qualifications

Experience in semiconductor manufacturing, industrial automation, robotics, medical imaging, or advanced inspection systems.

Knowledge of optical systems, cameras, sensors, and imaging hardware.

Experience with edge AI deployment and real-time inference systems.

Familiarity with SQL, Spark, Databricks, and distributed computing environments.

Increased process efficiency, yield, or product quality through AI-driven insights.

Successful deployment and adoption of vision solutions in production environments.

Technical leadership and influence across multiple engineering programs.

Core Competencies

Technical Leadership
Computer Vision & Deep Learning
Data Science & Analytics
Systems Thinking
Problem Solving
Innovation & Research
Cross-functional Collaboration

Our commitment

We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.

Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.

Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories – On-site Flex and Virtual Flex. ‘On-site Flex’ you’ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex’ you’ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.
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Our Perks and Benefits

At Lam, our people make amazing things possible. That’s why we invest in you throughout the phases of your life with a comprehensive set of outstanding benefits.