Function: Digital, Data & AI Engineering
Location: Petaling Jaya
Internship Duration: 3–6 months (flexible)
Role Purpose
The AI Engineer Intern will support the design, development, and deployment of AI- and automation‑driven solutions that improve efficiency, data quality, and decision‑making across the organisation. This role provides hands‑on exposure to AI engineering, automation pipelines, data processing, and applied machine learning in a real business environment.
Key Responsibilities
AI & Automation Development
- Support development of AI‑enabled solutions such as:
- Automation pipelines
- Intelligent reporting
- Data validation and enrichment workflows
- Assist in building and maintaining ETL / data pipelines using Python and automation tools.
- Support integration of AI or rule‑based logic into business processes to reduce manual effort.
Upskilling & Change Enablement Support
Contribute to GFS upskilling initiatives by supporting participants with technical skill needs before , after & during training (eg: guidance on tools , practice materials , troubleshooting etc.)
Machine Learning & Analytics
- Assist in developing, training, and testing machine learning models (where applicable).
- Support data preparation tasks including cleaning, transformation, and validation.
- Conduct performance checks on models or pipelines (accuracy, latency, reliability).
Workflow & System Integration
- Support workflow automation using tools such as n8n, APIs, or cloud‑based services.
- Help integrate multiple data sources (files, APIs, databases) into end‑to‑end pipelines.
- Assist in troubleshooting automation or data processing issues.
Documentation & Knowledge Sharing
- Create and maintain clear technical documentation for:
- Pipelines
- Models
- Automation workflows
- Support knowledge sharing through demos, walkthroughs, or capability-sharing sessions.
- Ensure solutions adhere to basic governance, security, and documentation standards.
Continuous Improvement & Innovation
- Participate in digital initiatives, pilots, or hackathon‑style projects.
- Proactively identify opportunities where AI or automation can improve efficiency or quality.
- Stay up to date with emerging AI tools, frameworks, and best practices.
Required Skills & Competencies
Technical Skills
- Strong foundation in Python.
- Working knowledge of:
- Data processing libraries (Pandas, NumPy)
- SQL (basic to intermediate)
- Exposure to machine learning frameworks (e.g. TensorFlow, PyTorch, scikit‑learn).
- Understanding of ETL concepts and data pipelines.
- Familiarity with APIs and basic system integration concepts.
- Experience with automation tools (e.g. n8n, scripts, schedulers) is an advantage.
- Basic knowledge of Git / version control preferred.
Core Skills
- Strong analytical and problem‑solving mindset.
- Ability to document technical solutions clearly and concisely.
- High attention to detail, especially around data quality.
- Self‑driven, curious, and eager to learn.
- Able to work independently while collaborating with cross‑functional teams.
Educational Background
- Undergraduate student in:
- Computer Science (AI / Data Science / Software Engineering)
- Data Analytics
- Information Systems
- or a related field
- Coursework or projects related to AI, ML, data engineering, or automation is preferred.
What the Intern Will Gain
- Hands‑on experience building production‑style AI and automation solutions.
- Exposure to real business use cases for AI in finance and operations.
- Strong grounding in AI engineering, data pipelines, and automation workflows.
- Opportunity to work with digital, finance, and transformation teams.
- Mentorship and structured learning in an enterprise environment.
