Micron is looking for a hands-on Staff / Principal Full Stack AI Engineer (Industrial AI) to design, build, and deploy production-grade AI applications that support Industrial AI and Autonomous Operations. This onsite role in Boise, ID spans the full delivery lifecycle, from data ingestion and AI modeling through APIs, web user experiences, digital twin integrations, and cloud and edge deployments.
How you’ll help build production AI for industrial operations
- 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, supported by backend services in Python and FastAPI.
- Develop scalable integrations between manufacturing systems, robotics platforms, AMRs, sensor networks, and enterprise applications to enable intelligent factory operations.
- Design and implement digital twin environments using NVIDIA Omniverse, Gazebo, or Unity Robotics Hub to support 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 computing environments.
- Optimize AI and simulation workloads through GPU acceleration, performance tuning, model optimization, and Responsible AI standards.
What you bring
- 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/TypeScript, with experience developing scalable software architectures.
- Experience building data ingestion, ETL, or feature engineering pipelines that support AI/ML applications at scale.
- Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP), Docker, Kubernetes, and CI/CD pipeline development.
- Working knowledge of SQL and database technologies used in enterprise application development.
- Experience collaborating with teams across software engineering, data science, operations, and infrastructure.
Benefits
- 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
Preferred qualifications
- 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, 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 critical/cleanroom environments.
Key technologies: React, Angular, Streamlit, Python, FastAPI, NVIDIA Omniverse, Gazebo, Unity Robotics Hub, LLMs, Docker, Kubernetes, CI/CD, AWS, Azure, GCP, SQL, JavaScript, TypeScript, ETL, GPU acceleration.
