Career Opportunities

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.

This success is the result of our employees' diverse technical and business expertise, which fuels close collaboration and ongoing innovation.

Join the Lam Research team, where you can write your own success story. Come help us solve our customers' toughest problems and be part of a company that plays a vital role in the future of electronics.

Lam Research - a company where successful people want to work.

Data Scientist 4

Date: Sep 1, 2020

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About Lam….

 

Together we move the Atoms that move the World:

Imagine working on the front lines of innovation! As one of the semiconductor industry's leading suppliers of wafer fabrication equipment and services, our technology depends on finding and hiring the best and the brightest employees. We know that our dynamic, global team of exceptional employees is essential to our continued growth.

 

Lam Research - where successful people want to work:

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. This is truly a rare opportunity. Lam Research is a market leader where our core values are not just words on the back of your badge. Given the criticality of this role to Lam Research's success, this philosophy starts with you.

Job Responsibilities

A technical expert who will be working with multi-dimensional datasets from various time-series sensors to develop generative and discriminative models. Your portfolio includes deploying deep learning methods with traditional computer vision to build robust image detection and feature recognition models, designing advanced deep learning (LSTM, RNN) for advanced process control, writing robust and maintainable code that is well documentation with version control in Python/R, identifying core requirements for image segmentation and creating and deploying apps while providing UX feedback. Responsibilities also include creating Python applications that parse and format large data sets for analysis, developing or specifying DB pipelines for image storage and data retrievability, helping with creating and deploying apps while providing UX feedback, working with, and supply models to process engineers for increase speed to solutions and developing or specifying DB pipelines for image storage and data retrievability.

Other Job Responsibilities
Minimum Qualification
  • Masters or PhD in Data Science, Computer Science, Electrical Engineering, Physics, Materials Science or related field
  • Min 1 - 2 years of experience with applied computer vision and machine learning algorithms and creating code for formatting large data sets in Python, C, or R within the semiconductor industry
  • Solid mathematics background (linear algebra, probability, optimization).
  • Knowledge in deep learning architectures for computer vision, and associated libraries and frameworks (Spark, Keras, Tensorflow, OpenCV, Skimage, etc.).
  • Experience with and implementing CNN’s, feature detection, and classification.
  • Experience with the utilization of operating system Linux or Unix.
  • Strong communication skills.
Preferred Qualification
  • Previous work analyzing multi-dimensional data, including segmentation, reconstruction, classification, or manipulation is a big plus
  • Experience with solr, and SQL or HDFS/HBase is a plus
More About Us ….

 

Our work is everywhere you look – even if you can’t actually see it. Lam Research goes deeper than software or chips to the heart of the process that enables chip creation. So if you want to help power the components that empower everything, join us.

 

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.

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