Algorithm Developer

Applied Materials•Santa Clara, CA

12h•Onsite

About The Position

Who We Are 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.

Requirements

Master’s degree in data science and engineering fields (e.g. Physics, Chemical Engineering, Mechanical Engineering, Electrical Engineering, etc.)
Good understanding of machine learning, deep learning or other statistical data analysis techniques, such as regression, time series analysis, hypothesis testing, classification, or clustering
Experience in data extraction & cleaning, signal processing, and visualization for large datasets
Confident programming skill of python with various data science packages , React, SQL and more
Able to conduct technical communication with colleagues from globe

Nice To Haves

PhD degrees with demonstrated achievement with time-series data analysis of machinery tools
Understanding of physical systems (e.g. signals processing, sensors, semiconductor process )
Experience developing data science methods for manufacturing problems

Responsibilities

Develop & Evaluate data science modeling (incl. ML/DL) algorithms using complex time-series sensor data collected from Semi Equipment
Perform algorithmic C&F for an algorithmic feature, including problem analysis, data gathering, literature review, concept selection and evaluation and implementation constrains
Develop executable data science solutions delivering differentiated insights to the engineering team
Working with SW engineering team to develop data pipeline / modeling pipeline that can be integrated with the Internal Applied platform
Fine tune algorithm performance, troubleshoot and resolve algorithm / modeling pipeline issues
Document algorithmic development, take part in planning and accompany implementation, integration and testing of an algorithmic module
Conduct technical communication with colleagues from multi-teams under fast-paced environment from C&F to productization