2026 Summer AI ML Intern - BS/MS (Gloucester, MA)

Applied MaterialsGloucester, MA
2d$37 - $45

About The Position

Applied Materials' VCS Software Engineering Department is searching for an intern to join our team for Summer 2026! Our department works on control systems for our business unit which builds ION implanters used in the manufacturing of computer chips, and power electronics. Specifically, our team works on improving performance using Artificial Intelligence and Machine Learning. We already have several patents and papers published - and are experimenting with cutting edge AI technology. The position will entail the following: Reducing very large (many TB) proprietary datasets to Parquet / Pandas formats for use in several new and ongoing AI projects Using both Cloud-based Cloudera infrastructure for developing and running AI experiments using Jupyter Notebooks Developing models from computer simulations to do digital twins Neural Nets - Reinforcement Learning, DNNs, CNNs, RNNs, LSTMs, ESNs and more Machine Learning - Bayesian Networks, Gaussian Process, SVMs, Random Forests, Isolation Forests Assisting physicists in exploring various AI projects.

Requirements

  • Student must be either a rising senior in a Bachelor's degree program or currently pursuing a Master's degree program in AI related field such as Computer Science, Physics or Engineering.
  • Student must be in good academic standing at their university, with a preferred GPA of 3.0 or above on a 4.0 scale
  • Quick learner - and willing to learn, or already familiar with Python and C

Responsibilities

  • Reducing very large (many TB) proprietary datasets to Parquet / Pandas formats for use in several new and ongoing AI projects
  • Using both Cloud-based Cloudera infrastructure for developing and running AI experiments using Jupyter Notebooks
  • Developing models from computer simulations to do digital twins
  • Neural Nets - Reinforcement Learning, DNNs, CNNs, RNNs, LSTMs, ESNs and more
  • Machine Learning - Bayesian Networks, Gaussian Process, SVMs, Random Forests, Isolation Forests
  • Assisting physicists in exploring various AI projects.
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