Senior AI Research Scientist

Overview of Role

TSMC is seeking applications for skilled Senior Artificial Intelligence (AI) Research Scientists for their Artificial Intelligence for Business Intelligence (AI4BI) Center. The AI4BI Center is a global and international team that develops advanced AI-enabled analytics techniques to facilitate important business intelligence applications highly relevant to TSMC. This role will be based in our San Jose office in a hybrid working environment (working four days in the office).

Individuals in this position may be responsible for tasks across two technical areas: designing and implementing significant machine learning, deep learning, text mining, Large Language Model (LLM), foundation model, 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 BI applications; and developing time series modelling and/or reinforcement learning-based approaches for analyzing fab tool productivity and facilitating effective wafer start strategies.

This role requires close interaction and coordination with international teams of junior AI research scientists, data engineers, and business stakeholders to gather requirements, oversee development, evaluate the outputs of technical solutions, produce internal reports, and lead co-authored publications at top-tier AI venues.

• Create and manage advanced machine learning, deep learning, LLM, foundation models, time-series modelling, and/or reinforcement learning algorithms to develop data-driven solutions for complex business problems
• Analyze and interpret complicated data sets to provide actionable insights that aid in enhancing decision-making processes for business stakeholders
• Work with cross-functional and international teams to identify and prioritize data-driven opportunities, including the development and deployment of predictive models to drive business outcomes
• Lead teams of junior data scientists and data engineers to develop efficient procedures, follow best practices, and provide implementation guidance (e.g., code reviews, demos) for gathering, retaining, and scrutinizing data
• Consistently assess and refine model performance to ensure precision and dependability
• Communicate insights and recommendations via internal reports to technical and non-technical stakeholders
• Design and implement the latest AI, machine learning, and data science tools and techniques to enhance existing processes
• Produce publications in leading AI conference and/or journal venues

• Ph.D. in computer science, information systems, information science, statistics, or related AI or machine learning field
• At least 7-10 years of significant AI, machine learning, and data science-related working and research experience
• Experience gathering requirements from business stakeholders and developing technical machine learning designs for implementation
• Strong practical experience with data wrangling, pre-processing, and extraction from structured and unstructured data sources
• Strong conceptual and practical knowledge and experience of classical machine learning algorithms and learning paradigms, including supervised learning and unsupervised learning
• Strong skills in deep learning implementation, including data encodings, processing units, and learning paradigms
• Proficiency in developing novel machine learning or deep learning algorithms based on unique dataset characteristics and business requirements
• Strong practical network science skills and experience
• Experience with text analytics for named entity recognition, sentiment analysis, and topic modelling
• Hands-on research experience with time series modeling and forecasting with statistical, machine learning, deep learning-based, and/or foundation model (Times
  
  FM) approaches
• Hands-on research experience with reinforcement learning approaches, including value-based, policy-based, actor-critic, and/or multi-objective
• Hands-on research experience, including literature review, model design, implementation, evaluation, and publication
• Experience fine-tuning LLMs and other foundation models…