AI Research Scientist

Overview of Role

Taiwan Semiconductor Manufacturing Company (TSMC) is seeking applications for skilled Artificial Intelligence (AI) Research Scientists for their Artificial Intelligence for Business Intelligence (AI4BI) Center. Applicants should have graduated with a Ph.D. in the past 1-2 years in computer science, information systems, information science, statistics, systems and industrial engineering, or related AI or machine learning field. The AI4BI Center is a global and international team that seeks to develop 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 machine learning, deep learning, text mining, large language model (LLM), foundation model, and/or network science-based approaches to extract insights from structured and unstructured data sources, as well as developing time series modelling and/or reinforcement learning-based approaches for analysing fab tool productivity and wafer start strategies.

This role requires close interaction and coordination with international teams of research scientists, data engineers, and business stakeholders to gather requirements, oversee development, evaluate outputs of technical solutions, produce internal reports, and co-author 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 datasets to provide actionable insights that aid in decision-making
• Work with cross-functional and international teams to identify and prioritize data-driven opportunities, including developing and deploying predictive models to drive business outcomes
• Collaborate with senior data scientists, other junior data scientists, and data engineers to develop and uphold efficient procedures for gathering, retaining, and scrutinizing data
• Work in teams with data engineers
• Continuously 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 based on feedback and guidance from senior data scientists

• Ph.D. in computer science, information systems, information science, statistics, or related AI or machine learning field in the past 1-2 years
• 4-5 years of AI/ML experience
• Proficient in Python, Git Hub, and Markdown for data wrangling, pre-processing, and extraction from structured and unstructured data sources
• Strong conceptual and practical knowledge of classical machine learning algorithms and learning paradigms (supervised and unsupervised)
• Strong skills in fundamental deep learning implementation, including data encodings, processing units, and learning paradigms
• Ability to adapt ML/DL algorithms to unique dataset characteristics and business requirements
• Strong practical network science skills and experience
• Hands-on experience with text analytics for named entity recognition, sentiment analysis, and topic modelling
• Hands-on research experience with time series modelling and forecasting using statistical, ML, DL, and/or foundation model (Times
  
  FM) approaches
• Hands-on research experience with reinforcement learning (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 with strategies such as low-rank adaptation and few-shot learning
• Experience with prompt engineering on LLMs and foundation models, including techniques such as reinforcement learning (e.g., DPO, PPO), prompt tuning, etc.
• Knowledge of deploying models into user-interface tools for dashboards (e.g., Power
  
  BI), Python frameworks for rapid prototyping (e.g., Streamlit, Dash), and/or JavaScript frameworks (e.g., React)
• Willingness to travel to Taiwan for at least 1-3 months each year for training, team building, and project coordination

• Knowledge of processing text in financial, accounting, and market analysis reports
• Multilingual text analysis using packages like Stanza, Polyglot, or Textflint
• Knowledge of graph embedding techniques (graph convolutional networks, graph attention networks, graph transformers) using packages such as Stellar Graph, PyG, or Deep Graph Library
• Understanding of neural information retrieval methods, including deep structured semantic models, entity resolution, and retrieval augmented generation (RAG)
• Familiarity with learning…