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

Job Title

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

Role Summary

Design, build, and deploy AI and machine learning solutions for semiconductor manufacturing to improve yield, quality, cycle time, reliability, and cost. Work with Product Engineering and cross-functional teams to productionize predictive models, agentic AI tools, and scalable data pipelines.

Provide technical leadership and train Citizen Data Scientists to adopt ML/AI best practices and deliver measurable engineering improvements.

Experience Level

Senior - Principal/Staff level. Posting indicates senior-level responsibilities and typically requires 6+ years of relevant industry experience.

Responsibilities

Key responsibilities include model development, AI agent design, data engineering, enablement, and cross-functional collaboration.

• Develop, validate, and deploy ML models for yield prediction, test-time optimization, reliability analysis, and process improvement.
• Design and implement agentic AI solutions to automate engineering workflows (yield analysis, root-cause investigation, report generation, test validation).
• Build scalable ML workflows and production inference pipelines integrated with enterprise systems.
• Acquire, cleanse, transform, and structure high-volume manufacturing, test, probe, and inline process data.
• Partner with deployment and architecture teams to ensure robust, scalable production implementations and monitoring.
• Mentor and enable Citizen Data Scientists via training, workshops, reviews, and technical guidance.
• Drive innovation initiatives, contribute to technical publications and patent disclosures, and keep current with ML/AI and semiconductor technology trends.

Requirements

Must-have technical skills, experience, and soft skills. Education degree details are listed under Education Requirements below.

• Minimum of 6 years of relevant industry experience in machine learning, data science, or AI solution development.
• Proven experience developing and implementing ML solutions in production environments, including model evaluation and continuous improvement.
• Strong programming skills in Python and familiarity with libraries such as Pandas, NumPy, and scikit-learn.
• Experience with supervised and unsupervised ML techniques, regression, decision trees, ensemble methods, and predictive modeling.
• Experience handling large-scale structured datasets and building end-to-end ML workflows and data pipelines.
• Familiarity with software development best practices and version control; ability to collaborate with engineering and IT teams for production deployment.
• Strong analytical, communication, presentation, and stakeholder-management skills; ability to explain technical concepts to non-technical audiences.

Preferred / nice-to-have:

• Experience in semiconductor manufacturing, yield engineering, test engineering, or manufacturing analytics.
• Experience with deep learning frameworks (TensorFlow, PyTorch) and LLM-based applications; familiarity with agent frameworks (LangChain, Semantic Kernel, etc.).
• Knowledge of MLOps practices (CI/CD for models, monitoring, lifecycle management) and cloud ML platforms (Azure ML, AWS SageMaker, etc.).
• Experience with workflow automation and enterprise collaboration tools (Power Automate, SharePoint, JIRA, Confluence).

Education Requirements

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 technical field.

About the Company

Company: Micron Technology

Headquarters: Boise, Idaho, USA

Micron Technology is a global leader in memory and storage solutions, dedicated to transforming how the world uses information. The company offers a diverse portfolio of high-performance DRAM, NAND, and NOR memory products under the Micron and Crucial brands. With a commitment to customer focus and technological innovation, Micron drives advancements in artificial intelligence, 5G, and other data-centric applications, empowering users to learn, communicate, and progress.