STAFF ENGINEER, AI ARCHITECT, SMAI
Micron Technology3 days ago
Hyderābād, IndiaStaff+
Responsibilities
- Define and architect scalable, production-ready cloud analytics, machine learning, and data science solutions for complex smart manufacturing problems.
- Lead technical architecture decisions covering system design, data models, platform standards, technical debt reduction, and lifecycle management.
- Provide subject matter expertise to troubleshoot critical technical issues and develop solutions across multiple projects.
- Collaborate with cross-functional teams, tiger teams, and technical working groups to deliver scalable architecture outcomes.
- Coach and mentor Data Scientists, AI Engineers, and AI Product Owners through technical reviews, knowledge sharing, and solution guidance.
Requirements
- Require 15+ years of IT experience in data technologies, including 5+ years architecting and delivering large-scale cloud data analytics and AI/ML solutions.
- Require hands-on experience with Google Cloud Platform or Microsoft Azure and on-premises enterprise platforms.
- Desired experience includes Agentic AI, Generative AI, OpenShift, Kubernetes, Solace, and distributed enterprise computing technologies.
- Require 5+ years of hands-on experience with Python, .NET, SQL, modern front-end technologies such as Angular, software engineering, and GitHub-based collaboration practices.
- Require strong analytical, problem-solving, written communication, presentation, stakeholder interaction, adaptability, and emerging-technology evaluation skills.
Tech Stack
Categories
About Micron Technology
Micron Technology designs and manufactures memory and storage semiconductors—DRAM, NAND, NOR and SSDs—sold to device makers, cloud providers, and embedded/automotive markets. Founded in 1978 and headquartered in Boise, Idaho, it operates globally and sells under the Micron and Crucial brands as a public company (NASDAQ: MU). Its products support data center, AI, mobile, and PC systems, including high-bandwidth and multichip packages for performance- and space-constrained applications.