Principal Data Scientist, TPG

Micron • San Jose, CA

1d • Onsite

About The Position

The Innovation, Technology and Products - Applied AI and Data Science organization builds AI, machine learning, and analytics systems for hard semiconductor engineering problems. We work directly with product engineering, reliability, test, manufacturing, and systems teams. Our engineers pair semiconductor domain knowledge with modern ML engineering, cloud platforms, and agentic AI. Everything we build is meant to run in production, not stop at a prototype. We are looking for a Lead Engineer, Applied AI and Agentic Systems. You will own the architecture and drive delivery of AI systems that engineers rely on every day. Problems will reach you vague. You will turn them into designs, plans, and working software. You bring depth in machine learning plus real strength in software engineering, cloud deployment, and agentic AI. You set direction, review designs, question assumptions, and grow the engineers around you. When a problem gets genuinely hard, you dig into the code alongside the team. If that sounds like your kind of work, we would like to meet you!

Requirements

• Bachelor's degree in Computer Science, Data Science, Electrical/Computer Engineering, Statistics, Mathematics, Physics, or a related technical field.
• 8 years of relevant experience, or equivalent practical experience.
• Led complex AI, ML, data science, or software engineering programs as technical lead, directing the work of other engineers.
• Hands-on machine learning and statistical modeling: supervised learning, feature engineering, validation, performance evaluation, and reading model behavior.
• Python fluency with PyTorch, TensorFlow, scikit-learn, or XGBoost.
• Shipped models into production — inference pipelines, APIs, CI/CD, monitoring.

Nice To Haves

• Master's degree or PhD in Computer Science or a related technical field, or equivalent experience.
• People leadership: mentoring engineers, developing careers, and forming team capability.
• Semiconductors, memory, storage, electronics, hardware systems, or advanced manufacturing.
• AI/ML deployed in cloud, hybrid, or on-prem environments — AWS, GCP, Azure, Kubernetes, OpenShift, or Docker.
• LLMs, RAG, and agentic workflows: agent frameworks, model gateways, knowledge graphs, enterprise search, MCP tool integration, or workflow orchestration.

Responsibilities

• Set the architecture and technical direction for our applied AI, ML, and agentic AI work.
• Design systems end to end: data pipelines, features, model development, evaluation, inference services, and monitoring.
• Build the models engineers act on — prediction, diagnosis, optimization, and decision support for semiconductor applications.
• Ship agentic AI for engineering analysis, knowledge retrieval, workflow automation, and decision support.
• Define the guardrails and evaluations that earn trust in it.
• Break wide-open challenges into roadmaps, turning points, and success criteria.
• Report progress, risk, and model limits plainly to engineers and executives.

Benefits

• Choice of medical, dental and vision plans
• Benefit programs that help protect your income if you are unable to work due to illness or injury
• Paid family leave
• Robust paid time-off program
• Paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Principal