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Experience
Experienced
About the role
This role sits within Micron's smart manufacturing organisation in Singapore, where the team is pushing toward autonomous operations using AI, analytics, digital twins and robotics. You would act as a senior technical lead, owning AI products from the ground up and working alongside data scientists, software engineers, robotics specialists and manufacturing leaders. It suits an experienced full-stack AI engineer who enjoys turning research ideas into production systems at enterprise scale.
What you'll do
Architect and build complete AI products, covering data pipelines, feature engineering, model training and inference, APIs, web apps and monitoring.
Create responsive front-end interfaces with React, Angular or Streamlit on top of Python/FastAPI services, with strong typing and test coverage.
Maintain modular application layers that connect live sensor, robotics and manufacturing data to dashboards and decision-support tools.
Integrate robotics platforms, autonomous mobile robots, tool automation and control systems into smart manufacturing applications.
Build digital twin environments with 3D fab layouts, AMR fleets and tool stations using platforms such as NVIDIA Omniverse, Gazebo or Unity Robotics Hub.
Connect smart manufacturing systems so structured operational data flows into AI pipelines and digital twins.
Embed LLMs and agentic AI frameworks into production workflows for manufacturing and engineering users.
Develop AI-assisted robotics orchestration and 3D-aware features using spatial data, equipment positioning, robot trajectories and fab maps to improve anomaly detection, routing and predictive maintenance.
Containerise AI and robotics services with Docker and deploy via Kubernetes, OpenShift and cloud-native platforms.
Package robotics software stacks, AI services and 3D rendering workloads as microservices for cloud, on-premises and edge environments.
Manage GPU-accelerated inference and real-time simulation workloads.
Improve AI application performance and cost through caching, batching, GPU utilisation, model quantisation and inference optimisation.
Validate digital twin and simulation scenarios against real operational constraints before production rollout.
Lead CI/CD, automated releases, monitoring, model evaluation, drift detection and AI application lifecycle management.
Apply responsible AI practices such as input validation, prompt-injection defence, PII/IP protection, model governance, auditability and compliance.
Improve AI platform scalability, reliability, maintainability, performance and cost efficiency.
Communicate descriptive, diagnostic, predictive and prescriptive analytics to support manufacturing decisions.
Develop and optimise machine learning, deep learning and statistical models for structured and unstructured data.
Conduct code reviews, mentor engineers and drive software engineering best practices.
Lead testing, debugging, technical documentation, installation and maint
Requirements
Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science or a related field, or equivalent industry experience
8+ years building and shipping production web, software, machine learning or AI applications end-to-end
Proven delivery in complex cross-functional environments spanning software engineering, data science, robotics, manufacturing, automation and infrastructure
Experience designing and deploying scalable AI applications, APIs and data-driven solutions in production
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
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