Work experience must have included: Experience with Python for data processing and machine learning workflows, including experience Jupyter, GitHub, and Markdown; Experience applying machine learning and deep learning techniques to extract insights from large-scale datasets, including practical use of modern LLMs including prompt engineering, model optimization, or fine-tuning; Experience designing data pipelines that integrate extracted and parsed data into downstream analytics or ML systems; Experience extracting structured information from unstructured sources using techniques such as regular expressions, entity recognition, and LLM-based extraction, and formatting into data structures, such as lists, trees, graphs, grids, and/or sequences; and Experience retrieving and processing data from RESTful APIs, with a strong emphasis on parsing and transforming semi-structured data formats (e.g., JSON, XML) into usable data pipelines or downstream applications. The Company supports a thriving ecosystem of global customers and partners with the industry's leading process technologies and a portfolio of design enablement solutions to unleash innovation for the global semiconductor industry.