Success Starts Here

As a leading global supplier of wafer fabrication equipment and services to the semiconductor industry, Lam Research develops innovative solutions that help our customers build smaller, faster, and more power-efficient devices.

We are a company comprised of people who work hard, deliver outstanding results and maintain a sense of humor during even the most challenging times. Our success results from our employees' diverse technical and business expertise, which fuels close collaboration and ongoing innovation. We know that our dynamic, global team of exceptional employees is essential to our continued growth.

Join the Lam Research team, where you can play a vital role in the future of electronics and write your own success story.

Engineering Intern 2

Date:  Sep 4, 2021

Fremont, CA, US, 94538

Req ID:  161469

Job Responsibilities

Work with Global Operations and Information IT Operations AI machine learning engineers and researchers to accelerate development of  Automated Vision Equipment for deployment globally.

Work with state-of-the-art tools and frameworks to build scalable and efficient distributed pipelines for data processing, dataset generation, model training and inference.

Develop, train and optimize Machine Learning and Deep Learning models using high performance compute to perform vision recognition tasks.

Create foundational and product specific assets that are both cloud native (Azure) and edge centric while being cloud agnostic, this individual would need to work at the intersection of  IT MLOps, Software Engineering, Data Visualization supporting Automated Vision Inspection (AVI) deliverables,

Join forces with IT engineering operations personnel on the implementation of an Automated Visual Inspection (AVI) system utilizing Data Fabric (SILK), Edge compute ML and Power BI visualization in 2021

Other Job Responsibilities

    • Produce and optimize machine learning model for feature differentiation
    • Generate useful visualizations using Microsoft BI, Origin, JMP, MATLAB, and other statistical software packages
    • Work as a team member with engineering to correlate surface morphology data and processing techniques
    • Support brainstorm and innovate high value industry 4.0 use cases
    • Provide input on communication and change management as needed, to help drive success
    • Review activities and offer suggestions for improvement that align with the latest thinking and technology

Minimum Qualifications

    • Experience developing Feature Pipelines and/or model development experience in Vision, data augmentation/automated labeling (with frameworks like PyTorch or a similar framework).
    • Strong Python programming experience, with demonstrated experience in package development, deploying software in a production setting, debugging
    • Strong in data/feature engineering and distributed processing with PySpark, Spark+98 etc.
    • Familiarity with full-stack software or data science development, Docker, Kubernetes etc.

Preferred Qualifications

  • Education – has BS degree or higher, or equivalent, in data analytics and machine learning

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.

All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.

We Look Forward to Your Application

As a Data Scientist Vision Engineer, you will play a pioneering role in process automation using robotic image and multi-sensor time-series data. Our goal is to advance machine and decision intelligence in Lam’s products and processes, empower our teams and accelerate innovation. Join our team that is building AI pipelines, tools and infrastructure to automate processes at sub-atomic level.

Nearest Major Market: San Francisco
Nearest Secondary Market: Oakland

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