Lead Data Scientist – Applied AI & Agentic Systems

Micron Technology, Inc.; San Jose (CA); On-site; USD 145,000 - 360,000; Full time

Benefits offered by this job

Medical plans

Dental plans

Vision plans

Paid time off

Paid holidays

Equity

Job summary

Micron Technology, Inc. seeks a Lead Engineer for Applied AI and Agentic Systems to own architecture and drive AI system delivery used daily by engineers. You will turn vague problems into concrete designs, plans, and working software, collaborating with product, reliability, test, and manufacturing teams.

The role requires depth in ML and strong software engineering, cloud deployment, and agentic AI, with leadership to grow teams and shepherd projects from concept to production.

Qualifications

• Bachelor's degree or equivalent in CS, data science, or engineering.
• 8+ years of relevant AI, ML, data science, or software programs with technical leadership.
• Hands-on ML methods: supervised learning, feature engineering, evaluation, deployment.

Responsibilities

• Set architecture and technical direction for applied AI, ML, and agentic AI work.
• Design end-to-end data pipelines, features, models, inference services, and monitoring.
• Build production models for prediction, diagnosis, optimization, and decision support for semiconductor apps.
• Ship agentic AI for engineering analysis, knowledge retrieval, workflow automation, and decision support.
• Define guardrails and evaluations to earn trust and maintain safety in AI systems.

Skills

Machine learning

Software engineering

Python

PyTorch

TensorFlow

CI/CD

Cloud deployment

XGBoost

Education

Bachelor's degree in CS or related field

Master's or PhD in CS or related field

Tools

AWS

GCP

Azure

Kubernetes

Docker

OpenShift

Job description

Micron Technology, Inc. seeks a Lead Engineer for Applied AI and Agentic Systems to own architecture and drive AI system delivery used daily by engineers. You will turn vague problems into concrete designs, plans, and working software, collaborating with product, reliability, test, and manufacturing teams.

The role requires depth in ML and strong software engineering, cloud deployment, and agentic AI, with leadership to grow teams and shepherd projects from concept to production.