INTERNSHIP DETAILS

Factory Analytics Integration Intern, AI Engineering for Smart Factory

CompanySeagate Technology
LocationGeorge Town
Work ModeOn Site
PostedJanuary 2, 2026
Internship Information
Core Responsibilities
Develop and deploy machine learning models using modern MLOps tools and enhance monitoring features for model performance. Collaborate with cross-functional teams to solve real factory problems using AI/ML.
Internship Type
full time
Company Size
16404
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Seagate is a leader in mass-capacity data storage. We’ve delivered more than four and a half billion terabytes of capacity over the past four decades. We make storage that scales, bringing trust and integrity to innovations that depend on data. In an era of unprecedented creation, Seagate stores infinite potential. Unlock the full value of your data today.
About the Role

About our group:

The Factory Analytics InTegration (FAIT) Team at Seagate is a cross-functional group supporting the Smart Factory initiative. We integrate and operate advanced AI/ML solutions for manufacturing, focusing on real-time analytics, predictive maintenance, and process optimization. FAIT team collaborates with business, engineering, and machine development teams to deliver scalable, reliable, and innovative solutions using the latest MLOps platforms and tools. Our mission is to maximize operational excellence and accelerate digital transformation across global factories.

About the role - you will:

  • Develop and deploy machine learning models using modern MLOps tools (e.g., MLflow, KServe, Docker, Kubernetes).
  • Build/Enhance Monitoring and Observability features for model performance in production, set up alerts for model degradation, and help automate retraining workflows.
  • Improve detection capabilities to reduce the risk of running degraded models in production.
  • Build reusable AI deployment components and processing steps for faster, more reliable model updates.
  • Collaborate with cross-functional teams to solve real factory problems using AI/ML.
  • Learn and apply best practices in experiment tracking, model registry, scalable deployment and model development/training.
  • Communicate project status and technical insights to the team and supervisor.
  • Participate in Scaled Agile development and delivery.

About you:

If you’re curious about how AI is used in real factories, this internship will give you direct experience with production-grade systems. if you have worked on deploying ML models, setting up monitoring/alerting, or automating model updates will have an edge. 

  • Strong interest in bringing machine learning applications into production in real factory environments.
  • Excellent teamwork, communication, and presentation skills.
  • Capable of prioritizing multiple tasks, managing conflicting deadlines, and working effectively in a dynamic environment.
  • Passionate about exploring and applying AI/GenAI to enhance tasks.
  • Fluent in English communication (Listening, Speaking, Writing, Reading).

Your experience includes:

  • Good knowledge of the fundamentals in software development.
  • Logical thinking and problem-solving skills.
  • Experience with development tools such as Python, Visual Studio/C#.
  • Familiarity with MLOps concepts such as experiment tracking, model registry, CI/CD, and containerization (Docker/Kubernetes) is an advantage.
  • Exposure to tools like MLflow, KServe, Prometheus, Grafana, or similar is a bonus.
  • Experience in operationalizing ML models (MLOps) will be an added advantage.
  • Experience in GenAI tools like ChatGPT, Copilots, Gemini, etc.

Location:

Our Penang office is located in Suntech at Cybercity, easily accessible via public transportation. Enjoy amenities such as an on-site gym, ping-pong and badminton facilities, and a café serving breakfast, lunch, and coffee. Prefer dining out? A public food court across the street offers a variety of delicious options.

 

Location: Penang Malaysia Suntech
Travel: None

Key Skills
Machine LearningMLOpsPythonDockerKubernetesAIReal-Time AnalyticsPredictive MaintenanceProcess OptimizationMonitoringObservabilityExperiment TrackingModel RegistryCI/CDGenAICollaboration
Categories
TechnologyEngineeringData & AnalyticsManufacturingSoftware
Benefits
On-Site GymPing-Pong FacilitiesBadminton FacilitiesCafé