The posting
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.
- Experience with 3D modeling, simulation environments, robotics software stacks, or spatial AI applications.
- 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
- Experience in semiconductor manufacturing, industrial automation, robotics, or smart manufacturing environments.
- Hands-on experience with digital twin platforms such as NVIDIA Omniverse, Gazebo, Unity Robotics Hub, Siemens Tecnomatix, Unreal Engine, or similar technologies.
- Experience with MLOps, LLMOps, enterprise AI platforms, or large-scale AI deployment environments.
- Familiarity with MES, Industrial IoT, advanced automation systems, or regulated high-reliability environments.
- Experience with 3D modeling, simulation environments, robotics software stacks, or spatial AI applications.
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.
