Staff/Principal AI Engineer, SMAI

Job Summary

Lead the Future of AI-Powered Manufacturing at Micron

Micron is accelerating its transformation toward Autonomous Operations through Artificial Intelligence, advanced analytics, digital twins, robotics, and intelligent automation. As a Staff/Principal Full-Stack AI Engineer, you will be a technical leader driving the strategy, architecture, and delivery of next-generation AI products that power smarter manufacturing across Micron's global network of fabs and assembly/test sites.

In this highly influential role, you will own AI solutions end-to-end—from data engineering, machine learning, and agentic AI systems to modern full-stack applications, digital twin platforms, robotics integration, and edge-to-cloud deployment. Working closely with data scientists, software engineers, robotics teams, and manufacturing leaders, you will transform innovative ideas into scalable, production-grade solutions that improve efficiency, increase automation, and enable intelligent decision-making at enterprise scale.

This is a unique opportunity to shape the future of AI in semiconductor manufacturing and directly contribute to Micron's vision of autonomous, data-driven operations worldwide.

Main Responsibilities

• Design, architect, and build end-to-end AI products, including data ingestion pipelines, feature engineering, model training and inference, APIs, web applications, and observability frameworks.

• Develop responsive front-end applications using React, Angular, or Streamlit, backed by Python/FastAPI services, with strong type-safe development and test coverage practices.

• Architect and maintain scalable, modular application layers that bridge real-time sensor, robotics, and manufacturing data with enterprise-facing dashboards and decision-support systems.

• Design and develop full-stack integration of robotics platforms, Autonomous Mobile Robots (AMRs), tool automation systems, and control systems with smart manufacturing applications and the Micron smart manufacturing ecosystem.

• Design and implement digital twin environments, including 3D representations of fab layouts, AMR fleets, and tool stations using platforms such as NVIDIA Omniverse, Gazebo, Unity Robotics Hub, or equivalent technologies.

• Interface with Smart Manufacturing systems to integrate structured operational data into AI pipelines and digital twin environments.

• Design and integrate LLMs and agentic AI frameworks into production workflows for manufacturing and engineering users.

• Develop AI-assisted robotics orchestration capabilities and 3D-aware AI features that leverage spatial data, equipment positioning, robot trajectories, and fab maps to improve anomaly detection, route optimization, and predictive maintenance.

• Containerize AI and robotics services using Docker and deploy solutions through Kubernetes, OpenShift, and modern cloud-native platforms.

• Package and deploy robotics software stacks, AI services, and 3D rendering workloads as containerized microservices supporting cloud, on-premises, and edge manufacturing environments.

• Manage GPU-accelerated inference workloads and real-time simulation environments supporting AI, robotics, and digital twin applications.

• Optimize AI application performance and cost through caching, batching, GPU utilization, model quantization, and inference optimization strategies.

• Validate digital twin and simulation scenarios against real-world operational constraints before production deployment to support safe and reliable autonomous operations.

Other Responsibilities

• Lead implementation of CI/CD, automated software releases, monitoring, model evaluation, drift detection, and AI application lifecycle management for production AI applications.

• Apply Responsible AI practices, including input validation, prompt-injection defense, PII/IP protection, model governance, auditability, and compliance requirements.

• Design and implement improvements to AI platform scalability, reliability, maintainability, performance, and cost efficiency.

• Develop and communicate descriptive, diagnostic, predictive, and prescriptive analytics to support manufacturing and operational decision-making.

• Develop, implement, and optimize machine learning, deep learning, and statistical models for structured and unstructured data.

• Perform code reviews, provide technical mentorship, and drive software engineering best practices across project teams.

• Lead testing, debugging, technical documentation, installation procedures, and maintenance strategies for AI and software solutions.

• Integrate AI-assisted tools and insights into daily work to improve efficiency, quality, and effectiveness while complying with organizational standards, legal requirements, and governance policies.

• Contribute to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one's scope of work.

Minimum Required Qualifications / Experience

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field; equivalent industry experience accepted.

• 8+ years building and shipping production web, software, machine learning, or AI applications end-to-end.

• Track record of delivering solutions in complex cross-functional environments spanning software engineering, data science, robotics, manufacturing, automation, and infrastructure teams.

• Experience designing and deploying scalable AI applications, APIs, and data-driven solutions in production environments.

Must Have Technical Skills

• Expert programming skills in Python and modern JavaScript/TypeScript, with experience designing scalable software architectures.

• Strong SQL proficiency and experience designing data ingestion and feature engineering pipelines for AI/ML workloads at scale.

• Experience with Docker, Kubernetes/OpenShift, cloud platforms (AWS, Azure, or GCP), and CI/CD pipeline ownership.

• Experience with machine learning, deep learning, statistical modeling, predictive analytics, and large-scale computing frameworks.

• Strong knowledge of GenAI technologies, including prompt engineering, function/tool calling, Retrieval-Augmented Generation (RAG), LLM integration, agentic AI patterns, model evaluation, and Responsible AI practices.

• Experience working with distributed data processing platforms, enterprise AI systems, and production AI operations.

• Ability to apply AI literacy and digital fluency to use AI-enabled tools responsibly and effectively for research, analysis, content creation, problem-solving, operational tasks, automation, and achieving business outcomes.

Must Have Soft Skills

• Strong analytical and problem-solving skills.

• Excellent communication and stakeholder management skills.

• Ability to influence technical decisions across cross-functional teams.

• Strong collaboration, ownership, and execution mindset.

Highly Desirable / Preferred Skills or Experience:

• Master’s degree in Computer Science, Artificial Intelligence, Robotics, Data Science, or a related field, or equivalent experience.

• Prior experience in semiconductor manufacturing, advanced manufacturing, industrial automation, digital twin development, or other high-reliability operational environments.

• Experience implementing Generative AI solutions, including RAG architectures, prompt engineering, function/tool calling, agentic workflows, and LLMOps practices.

• Experience applying Responsible AI, security, audit logging, and model governance practices within production applications.

• Knowledge of GPU-accelerated computing, model optimization techniques, and deployment of AI workloads in cloud and edge environments.

• Hands-on experience with digital twin and simulation platforms (NVIDIA Omniverse, Gazebo, Unity Robotics Hub, Siemens Tecnomatix, Unreal Engine) and the Autodesk stack (Revit, Navisworks, ACC, ReCap), including point-cloud processing, photogrammetry, Gaussian splatting, and geometry optimisation via IFC and Revit APIs.

• Experience integrating robotics, autonomous mobile robots (AMRs), industrial automation, and IoT sensor networks into software applications, with proven robotics development in ROS/ROS 2 and Isaac Sim/Lab — including SLAM perception, LiDAR/depth-camera data processing, and sim-to-real transfer (imitation learning, domain randomization).

• Proven experience in integration of SCADA/FMCS/BMS systems for smart facilities and EHS , ideally in semiconductor, data center, pharmaceutical, or other mission-critical/cleanroom environments

Embody Micron's Core Values

• People – Respect, develop, and empower others.

• Innovation – Drive continuous improvement and breakthrough thinking.

• Tenacity – Show grit and determination.

• Collaboration – Build trust and foster teamwork.

• Customer Focus – Deliver excellence and value.

• Speed – Act with purpose and set the pace.