Principal/Staff ML/AI Engineer, Product Engineering, STPG
Micron seeks a Principal/Staff ML/AI Engineer in Singapore to build predictive ML models and agentic AI solutions for semiconductor product engineering — improving yield, test time, and automation — while mentoring citizen data scientists. Core stack: Python (Pandas, scikit-learn), TensorFlow/PyTorch, LangChain/Copilot Studio, MLOps, and Azure ML/SageMaker.
- Compensation
- Not disclosed
- Location
- Singapore
- Work setup
- Onsite
- Seniority
- Principal
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- Bachelor's or Master's in Computer Science, EE, Data Science, or related field with at least 5 years of ML/AI development experience
- Strong proficiency in Python and data processing libraries (Pandas, NumPy, Scikit-learn)
- Experience with ML algorithms for structured data: regression, tree-based models, gradient boosting
- Ability to build and evaluate ML models for predictive analytics
- Experience with ML frameworks (TensorFlow, PyTorch) for unstructured data (images, text, logs) and scalable model deployment
- Exposure to agentic AI concepts and frameworks (LangChain, Microsoft Copilot Studio)
- Understanding of LLM-based solutions and their integration into enterprise applications
- Knowledge of MLOps practices: model lifecycle management, CI/CD for ML, production inference workflows
- Awareness of distributed computing and cloud AI services (Azure ML, AWS SageMaker)
- Strong problem-solving and analytical thinking
- Excellent communication and cross-functional collaboration with semiconductor SMEs and management
Nice to have
- PhD in a related field with at least 3 years of practical experience (alternative path)
- Semiconductor industry or manufacturing analytics background
- Hands-on experience with AI agents or workflow automation
- Knowledge of enterprise integration tools (Power Automate, SharePoint connectors)
Full description
Our vision is to transform how the world uses information to enrich life for all.Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.
About the Role:
Join our Product Engineering team to develop AI and Machine Learning solutions that transform semiconductor workflows. This role focuses on model development and agentic AI applications, enabling smarter testing, faster yield advancement, and engineering automation to improve cost, cycle time, and quality. This is a ground-breaking opportunity to work on modern technologies and make a significant impact in a world-class company!
You will also train and guide Citizen Data Scientists (CDS or equivalent experience) within Product Engineering, helping them apply advanced ML techniques and analytics tools to gain domain-specific insights.
Key Responsibilities:Machine Learning Development:
- Build predictive models for yield, test time, and reliability analysis using structured/tabular data
- Use advanced machine learning techniques to analyze complex datasets and generate actionable insights that improve manufacturing and operational performance
- Build and validate ML workflows for large-scale semiconductor datasets
Agentic AI Solutions:
- Develop intelligent agents to automate engineering tasks (e.g., test program validation, yield analysis, report generation)
- Integrate agents with enterprise tools (JIRA, Confluence, SharePoint) and internal systems.
Data Engineering & Integration:
- Work with cross-functional teams to access, clean, and structure high-volume probe and wafer fabrication inline data to generate insightful information for ML/AI applications
- Collaborate with the inferencing architecture team during deployment phases to ensure successful and balanced production integration
Innovation & Collaboration:
- Find areas where AI can help reduce test time (TTR), improve yield, and automate processes
- Contribute to technical papers, patents, and internal guidelines
Citizen Data Scientist Enablement:
- Guide and upskill Citizen Data Scientists (CDS) in applying advanced ML techniques, guidelines, and analytics tools
- Build structured learning paths and hands-on training modules to strengthen CDS capabilities in machine learning and data-driven problem solving