Principal/Staff ML/AI Engineer, Product Engineering, STPG - Fab 10N/X, Singapore

Originally posted 1 October 2026 by the employer.

About the role

This role involves developing and deploying Artificial Intelligence (AI) and Machine Learning (ML) solutions to transform semiconductor manufacturing and engineering workflows, with a focus on improving yield, quality, and cost efficiency.

What you'll do

• Develop, validate, and deploy machine learning models for yield prediction, test time optimization, reliability analysis, and manufacturing process improvement.
• Apply advanced analytics and machine learning techniques to large-scale structured and semiconductor manufacturing datasets.
• Build scalable ML workflows and predictive solutions that generate actionable engineering insights.
• Design and develop intelligent AI agents to automate engineering and operational workflows.
• Partner with engineering teams to acquire, cleanse, transform, and structure high-volume manufacturing, test, probe, and inline process data.
• Mentor and coach Citizen Data Scientists in applying machine learning methodologies and analytics best practices.

What you'll need

• PhD with ≥2 years, or Master’s degree with ≥5 years, or Bachelor’s degree with ≥7 years of relevant experience in Computer Science, Data Science, Electrical/Electronic Engineering, Artificial Intelligence, or a related field.
• Minimum of 6 years of relevant industry experience in machine learning, data science, or AI solution development.
• Proven experience developing and implementing machine learning solutions in production environments.
• Experience working with large-scale structured datasets and predictive analytics applications.
• Strong programming skills in Python.
• Proficiency with data analytics and machine learning libraries such as Pandas, NumPy, Scikit-learn, and related tools.
• Experience with regression models, decision trees, random forests, gradient boosting, and predictive modeling.

Nice to have

• Semiconductor manufacturing, product engineering, yield engineering, test engineering, or manufacturing analytics experience.
• Experience with TensorFlow, PyTorch, or similar deep learning frameworks.
• Hands-on experience developing AI agents and agentic AI solutions using frameworks such as LangChain, Microsoft Copilot Studio, Semantic Kernel, or similar technologies.
• Experience building and integrating LLM-based applications into enterprise environments.
• Knowledge of MLOps practices including model lifecycle management, CI/CD pipelines, model monitoring, and production deployment.
• Experience with cloud-based AI and machine learning platforms such as Azure Machine Learning, Azure AI Services, AWS SageMaker, or equivalent.
• Knowledge of distributed computing and scalable inference architectures.
• Experience with workflow automation platforms such as Power Automate and enterprise collaboration platforms including SharePoint, JIRA, and Confluence.
• Experience training, mentoring, or leading Citizen Data Scientist programs and analytics communities.

Skills: machine learning, yield prediction, Python, ML workflows, semiconductor manufacturing datasets