Principal Full Stack AI Engineer; Industrial AI

Micron is seeking a hands-on Full-Stack AI Engineer to build production-grade AI applications for Industrial AI and Autonomous Operations
. This role spans the full lifecycle, from data ingestion and feature engineering to models, APIs, and user-facing applications, with deployment across cloud and edge environments.

Based in Boise,  (onsite), this position supports intelligent factory operations through integrations with manufacturing systems and robotics platforms, alongside digital twin environments and simulation-driven optimization.

• Design, architect, and deliver end-to-end AI products, including data ingestion pipelines
  , feature engineering
  , model training and inference
  , APIs
  , user interfaces
  , and application monitoring
  .
• Build and maintain modern front-end applications using React
  , Angular
  , or Streamlit
  , backed by services in Python and FastAPI
  .
• Develop scalable integrations across manufacturing systems
  , robotics platforms
  , AMRs
  , sensor networks
  , and enterprise applications to enable intelligent operations.
• Design and implement digital twin environments using NVIDIA Omniverse
  , Gazebo
  , or Unity Robotics Hub for simulation, validation, and operational optimization.
• Integrate LLMs
  , agentic AI frameworks
  , and AI-assisted decision support into production manufacturing workflows.
• Deploy and manage containerized applications using Docker
  , Kubernetes
  , and CI/CD pipelines across cloud and edge
  .
• Optimize AI and simulation workloads using GPU acceleration
  , performance tuning, model optimization, and Responsible AI standards
  .

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical field, or equivalent professional experience.
• 5+ years of experience designing, building, and deploying production web applications, AI solutions, or both.
• Strong programming skills in Python and modern JavaScript/Type Script , with experience building scalable software architectures.
• Experience creating data ingestion
  , ETL
  , or feature engineering pipelines that support AI/ML at scale.
• Hands‑on experience with at least one major cloud platform (
  AWS
  , Azure
  , or GCP
  ), plus Docker
  , Kubernetes
  , and CI/CD development.
• Working knowledge of SQL and database technologies used in enterprise application development.
• Ability to collaborate across teams including software engineering, data science, operations, and infrastructure organizations.

• Choice of medical, dental, and vision plans in all locations
• 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

• Master’s degree in Computer Science, Artificial Intelligence, Robotics, Data Science, or a related field, or equivalent experience.
• 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 deploying AI workloads in cloud and edge environments.
• Hands‑on experience with digital twin and simulation platforms, including NVIDIA Omniverse
  , Gazebo
  , Unity Robotics Hub
  , Siemens Tecnomatix
  , and Unreal Engine
  , plus Autodesk stack tools (
  Revit
  , Navisworks
  , ACC
  , Re Cap ) including point‑cloud processing, photogrammetry, Gaussian splatting, and geometry optimization via IFC and Revit APIs
  .
• Experience integrating robotics, autonomous mobile robots (AMRs), industrial automation, and IoT sensor networks into software applications, including robotics development in ROS/ROS 2 and Isaac Sim/Lab
  , plus SLAM perception, LiDAR/depth‑camera data processing, and sim‑to‑real transfer (imitation learning, domain randomization).
• Proven experience integrating SCADA/FMCS/BMS systems for smart facilities and EHS, ideally in semiconductor, data center, pharmaceutical, or other critical/cleanroom environments.