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Taichung City, Taiwan
Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an 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 the Company began construction on a specialty technology fab in Dresden, 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. The Facility Computer Integrated Manufacturing Department (FDCIM) is part of the Intelligent Manufacturing Center (IMC) at TSMC. It is primarily responsible for the development and maintenance of the following products: Development and maintenance of manufacturing-related report products for wafer fabs.Development and maintenance of engineering-related report products for wafer fabs.Development and maintenance of digital operation system products for facility management.Development and maintenance of big data application system products for facility management.Development and maintenance of facility management AI and machine learning related algorithm development and application system products. Responsibilities: FDCIM also employs software engineering and modular development techniques, combined with high-performance database application technologies, to develop systematized software with a unified version control system that accommodates different time zones and languages globally.In addition to its regular software product development work, FDCIM is also engaged in the research and development of new technologies, including the application of DevOps, Microservices, MLOps, AIOps, and more. Develop and maintain AI/ML systems and algorithmsCollaborate with cross-functional teams to identify and solve business problems using AI/ML techniquesDesign and implement machine learning models and data pipelinesTest and validate AI models for accuracy, scalability, and efficiencyDeploy AI solutions to production environmentsStay up-to-date with the latest advancements in AI technologies and industry trendsWrite clean and efficient code using HTML, CSS, and JavaScriptOptimize web applications for speed and scalabilityTest and debug web applications across multiple browsers and devicesStay up-to-date with the latest front-end development trends and best practices
Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an 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 the Company began construction on a specialty technology fab in Dresden, 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. As an AI/ML Engineer, you will be a key member of a versatile team focusing on both algorithm development and platform implementation for TSMC’s RD, Fab, Business, IT, and Security functions to improve productivity and work quality. The role involves developing AI/ML solutions, implementing scalable platforms to support AI productionization, and maintaining the lifecycle of machine learning models. Responsibility:Common Responsibilities1. Collaborate with cross-functional teams of data scientists, ML engineers, and software developers. 2. Drive the complete AI solution development stages from data collection, exploration, and feature engineering to model evaluation and error analysis.3. Perform model lifecycle management to ensure the validity of models in production. 4. Exercise sound judgment in determining if business problems can be addressed through AI/ML and communicate results effectively to domain users. 5. Operate and maintain scalable, highly available AI platforms with continuous measurement and quality improvement to meet SLO/SLAs. Differentiated Responsibilities1. AI/ML Solution Development(1) Develop AI/ML algorithms that optimize manufacturing processes, improving productivity and work quality. (2) Explain AI/ML models to internal customers and conduct error analysis.2. AI Platform Development (1) Design and implement full tech stack solutions, including data-related technologies and AI platforms.(2) Develop tools, automation, and microservices to extend platform capabilities. (3) Manage container-based workloads and process high volumes of data in environments like Kubernetes.Additional information for the job: Job Location: Hsinchu Site, Taipei Office (Experienced only)On-call needs: On-call 1 week every 3 months The complete interview process includes:1. Manager interview2. Hackerrank test3. On-site personality and English test(which could be replaced if you have script of officially English test) 4. HR interview5. Second manager interview (Optional assessment)6. Technical review (Optional assessment)
台灣新竹市新竹
TGC Europe
Negotiable
No requirement for relevant working experience
No management responsibility
Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an 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 the Company began construction on a specialty technology fab in Dresden, 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.Advanced Quality System Development (AQSD) is part of TSMC's Intelligent Manufacturing Center (IMC), responsible for three main directions: Use statistical methods and conditional monitoring to inspect fab control charts, providing early warning of abnormal product yields; offer a fab defense system settings comparison platform to check that machines meet the internal control anomaly conditions set by the engineering department.Develop online fab analysis platforms through Big Data, Machine Learning, and Deep Learning techniques for online yield/defect analysis to ensure the quality of wafers produced in the fab.Develop systems and provide logical operations to control and implement escape mechanisms for material batch changes, measurement stages, and inspection stages, ensuring quality and optimizing product sampling rules. Responsibilities: Apply machine learning/optimization algorithm to build up models for optimizing semiconductor production.Develop analysis and optimization methods to enhance product quality, increase tool productivity and improve people productivity.Design, develop and test prediction models with real applications in manufacturing.Build a flexible framework to speed up the development process of AI models, with a focus on Large Language Models (LLMs) serving.Turn exciting AI prototypes/ideas into products, leveraging LLMs and other advanced AI technologies.Develop next-generation AI backend systems related to large-scale real-time data access, collection, analytics and monitoring.Establish and maintain MLops processes and tools, including model deployment, monitoring, and automation.Continuously improve the quality of AI production systems, particularly those utilizing LLMs.
Negotiable
No requirement for relevant working experience
Managing staff numbers: not specified

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