Principal/Staff ML/AI Engineer, Product Engineering, STPG

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

• Serve as a mentor to offer continuous support, evaluate work, and suggest methods for AI initiatives within Product Engineering.

Requirements

Education:

• Bachelor's or Master's degree in Computer Science, Electrical/Electronic Engineering, Data Science, or a related field with at least 6 years of experience in machine learning/AI development and implementation

• PhD in a related field, accompanied by at least 3 years of practical experience in application (or a combination of research and industry involvement)

Core Technical Skills:

• Strong proficiency in Python and data processing libraries (e.g., Pandas, NumPy, Scikit-learn)

• Experience with machine learning algorithms for structured data, including regression techniques, tree-based models, and gradient boosting frameworks

• Ability to build and evaluate ML models for predictive analytics

Additional Skills:

• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) for processing unstructured data (images, text, logs) and scalable model creation and deployment

• Exposure to agentic AI concepts and frameworks (e.g., LangChain, Microsoft Copilot Studio) for building autonomous workflows and orchestration

• Understanding of LLM-based solutions and their integration into enterprise applications

• Knowledge of MLOps practices, including model lifecycle management, CI/CD for ML, and production inference workflows for robust deployment

• Awareness of distributed computing and cloud-based AI services (e.g., Azure ML, AWS SageMaker) for scalable inferencing.

Soft Skills:

• Strong problem-solving and analytical thinking

• Excellent communication and ability to work in cross-functional teams with semiconductor subject-matter experts for technical exchange and management updates

Preferred Experience:

• Semiconductor industry or manufacturing analytics background

• Hands-on experience with AI agents or workflow automation

• Knowledge of enterprise integration tools (Power Automate, SharePoint connectors)

Why Join Us

• Drive AI innovation in semiconductor product engineering

• Work on high-impact projects that improve yield, reduce test time, and accelerate time-to-market

• Collaborative environment with opportunities for career growth, patent contributions, and technical leadership