Engineer I (Multiple Openings) at Samsung Ads · 12100…

Summary: Samsung Austin Semiconductor is a world leader in advanced semiconductor technology, committed to innovation. The Engineer I role involves detecting yield loss and implementing preventive measures while utilizing statistical analysis and machine learning to evaluate product characteristics and improve fabrication processes. Responsibilities: - Detect systematic, random yield loss, and drive fab engineering team to implement preventive measures - Use statistical analysis, semiconductor process, device physics knowledge, coding, and machine learning - Evaluate the product characteristics from the perspectives of circuit design to semiconductor process and device physics to identify the root cause of detected yield losses - Utilize the statistical analysis tools to find fab commonality, deep dive into electrical test data and tool parameters to segregate good and affected material at suspected timeframe - Evaluate process changes and check for statistical significance to wafer sort testing to provide clear direction to Fab for effectiveness and risk of change points - Derive a model for defects, share the results with the responsible department, and carry out the management of improvement items - Code significant change items and other relevant factors into the baseline production yield model to establish appropriate yield targets and deliver clear yield forecasts to fabrication teams Required Qualifications: - Master's degree in Computer Science, Data Science, Computer Engineering, or a related field - Completion of a graduate-level course, research project, or internship involving Python proficiency in algorithms and data analysis with Numpy, Pandas, Scikit-learn, Matplotlib, Plotly - Bigdata management proficiency with PostgreSQL, Spark and Hadoop - Statistics, including parametric inference, non-parametric inference, hypothesis testing, Bayesian inference, stochastic processes, bootstrap, and correlation coefficient for advanced data analysis, data modeling and robust model evaluation - Deep Learning algorithms in Image Processing and NLP fields with modern frameworks like PyTorch and Tensorflow - Classical machine learning algorithms (bagging, boosting) and regression models - Data visualization skills to generate 2D and 3D plots with Matplotlib and Plotly - Design of Experiment (DOE) Establishment and Verification - Key Item Management - R proficiency in data processing, data analysis, and web development Required Skills: Python, Bigdata management, Statistics, Deep Learning Important Skills: Data visualization, Design of Experiment, R proficiency Nice-to-Have Skills: Key Item Management Benefits: Medical, dental, and vision insurance, Life insurance and 401(k) matching with immediate vesting, Onsite café(s) and workout facilities, Paid maternity and paternity leave, Paid time off (PTO) + 2 personal holidays and 10 regular holidays, Wellness incentives and MORE