Data Science Engineer, New College Grad- Master's/PhD (Santa Clara, CA)
About The Position
Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world. The position requires implementing, deploying, maintaining, evaluating, and benchmarking data science and software ideas and techniques that differentiate Applied Service offerings using semiconductor process data. The person will implement prototype user interfaces which host the advanced algorithms; and deploy, test, analyze, and troubleshoot these applications worldwide at service sites. The position will entail the following: Assist in developing data science software prototypes and interfaces for monitoring semiconductor process tools Develop Python scripts to implement key concepts Deploy and maintain prototypes at service sites Collaborate closely with algorithm developers to characterize the algorithms and benchmark their performance, collecting quantitative data assessing effectiveness Evaluate the effectiveness and accuracy of the algorithms by working closely with process and equipment experts, providing feedback to algorithm developers Translate algorithms from one language to another (e.g., from MATLAB to Python) Knowledge and application of statistical / data science techniques, including both conventional Machine Learning, i.e., decision trees, regression Experience with various Artificial Intelligence Solutions, including Large Language Models, Computer Vision and Generative AI applications. Communicate and train field engineers on how to use prototype applications, including writing documentation and creating audio and video tutorials for use for a variety of user types Be able to interpret data science conclusions and relate to practical process issues
Requirements
- Python, MATLAB
- Familiarity with common data science techniques, including regression, decision trees, Principle components, PLS, various Neural networks, time-series techniques, Bayesian techniques, etc.
- Ability to troubleshoot software applications and perform basic DevOps for deployment
- Ability to interact with Process and Customer Engineers
- Master's or PhD in Computer Science, Data Science, Software Engineering, Mechanical Engineering, or related field.
- Preferred GPA of 3.0 or above
Nice To Haves
- Semiconductor process or equipment experience preferred.
Responsibilities
- Provide solutions which can be implemented by engineers without a deep statistical or mathematical background
- Deploy and maintain solutions at service sites
- Troubleshoot solutions, provide workarounds, and assist users in using solutions
- Assess effectiveness of solutions and provide data science insight
- Communicate well with algorithm developers and process experts
- Train field engineers to use solutions
- Present work and conclusions clearly and succinctly to peers
- Work well in team, providing and receiving constructive input with team members
- Monitor and quantify the results of complex algorithms in a production environment.
- Train a variety of individuals on the operation of these algorithms.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
