Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. In 2023, the company served 528 customers with 11,895 products for high performance computing, smartphones, IoT, automotive, and consumer electronics, and is the world’s largest provider of logic ICs with annual capacity of 16 million 12-inch equivalent wafers. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and its ESMC subsidiary plans to begin construction on a fab in Germany in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade.

We are a global and international team that seeks to develop advanced AI-enabled analytics techniques to facilitate important business intelligence applications highly relevant to TSMC. Individuals in this position will be responsible for designing and implementing significant machine learning, deep learning, text mining, Large Language Model (LLM), and/or network science-based approaches to extract insights from structured (e.g., transactional) and unstructured data sources (e.g., 10K reports, social media posts, news) for various applications. This role requires close interaction and coordination with international teams of data scientists, other data engineers and business stakeholders to gather requirements, oversee development, evaluate the outputs of technical solutions, produce internal reports, and co-author publications at top-tier AI venues.

1. Master’s degree or above in Computer Science, Information Systems, Information Science, or a related AI or Machine Learning field.

2. Proficient in Python, GitHub, and Markdown for data wrangling, pre-processing, and extraction from structured and unstructured data sources.

3. Experience connecting to REST API endpoints, particularly in parsing data in JSON and XML formats.

4. Experience developing web crawlers to collect data from web pages using tools such as Scrapy and BeautifulSoup.

5. In-depth knowledge of relational data management, including extracting, transforming, loading, and querying from MySQL databases.

6. Familiarity with server-based front-end/UI technologies, including HTML/CSS/PHP.

Preferred Qualifications:

1. 4-5 years of AI/ML experience (including those attained during Ph.D. studies) is a plus.

2. Implementation and operationalization of Big Data technologies, including Hadoop and Spark for unstructured, non-transactional data.

3. Experience working with NoSQL databases, including Elasticsearch for documents and Neo4j for graph-structured data.

4. Knowledge on how to extract content (e.g., with regular expressions, entity extraction) from unstructured data and format the extractions into data structures such as lists, trees, graphs, grids, and/or sequences.

5. Experience deploying machine learning and deep learning pipelines with serverless front-end/UI technologies, including Streamlit and Netlify.

6. In-depth knowledge of conventional machine learning and deep learning algorithms and packages, including scikit-learn, Keras, and/or Pytorch.

7. Deep understanding of finance, accounting, and market analysis.