Staff/Principal AI Engineer, SMAI

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE. LTD.; Singapore; Sur place; SGD 180 000 - 260 000; Plein temps

Résumé du poste

Micron is seeking a Staff/Principal Full-Stack AI Engineer to lead AI-powered manufacturing initiatives. You will own architecture, data pipelines, model training, and production systems across global fabs and assembly sites.

You will collaborate with data scientists, software engineers, robotics teams, and manufacturing leaders to deliver scalable AI solutions, digital twins, and edge-to-cloud deployments that drive efficiency and automation at enterprise scale.

Qualifications

• Experience designing and delivering AI-powered manufacturing solutions.
• Strong background in data engineering, ML, and AI systems integration.
• Proficiency with full-stack app development and cloud-native deployments.

Responsabilités

• Design, architect, and build end-to-end AI products including data ingestion, feature engineering, model training and inference, APIs, web apps, and observability.
• Develop responsive front-end apps using React/Angular/Streamlit with Python/FastAPI back-end services.
• Bridge sensor, robotics, and manufacturing data to dashboards and decision-support systems.
• Integrate robotics platforms and tooling with smart manufacturing ecosystems.
• Create digital twin environments using platforms like NVIDIA Omniverse, Gazebo, or Unity Robotics Hub.
• Interface with Smart Manufacturing systems to feed AI pipelines and twins.
• Design and embed LLMs and agentic AI workflows for production use.
• Lead CI/CD, automated releases, monitoring, drift detection, and lifecycle management.
• Apply Responsible AI, governance, and compliance considerations.
• Optimize AI apps for performance and cost; validate scenarios against real constraints.

Description du poste

Staff/Principal Full-Stack AI Engineer, IPAI, 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.