aimlroles

[Keppel Internship Programme 2027] Intern, Data/AI Engineering (Jan - May 2027)

Keppel Open · verified Oct 22, 2026
Singapore Full-time Junior AI Engineering

At a glance

Junior AI Engineering role at Keppel. Singapore · full-time.

Pay not stated AI Engineering salary

RoleAI Engineering
SeniorityJunior
LocationSingapore
EmploymentFull-time
PostedJul 28, 2026 · 2mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build and look after data pipelines that support the team's data work
  • Help develop and deploy machine learning models
  • Contribute to data platform work and AI or agent-based solutions

What you bring

  • You are pursuing a degree in computer science, data science, engineering or a related discipline
  • You have programming and SQL fundamentals, preferably including Python
  • You understand data structures, algorithms and software engineering basics
  • You know core data processing practices, such as ETL, modeling and cleaning, plus machine learning fundamentals
  • You can work with SQL or NoSQL databases and understand data warehousing concepts

Who this fits

This internship suits a student looking for practical work on data pipelines, machine learning and AI solutions. You'll work with analytics and business stakeholders as part of cross-functional teams.

From the employer

JOB DESCRIPTION

Keppel is a leading global asset manager and operator with strong capabilities in energy & environment, urban development and connectivity, creating solutions for a sustainable future. The intern will be responsible in the following: 'Build & Maintain Data Pipelines Support AI/ML Model Development & Deployment Contribute to Data Platform & AI/Agentic Solutions Learning Outcomes: 'Understand how large-scale data platforms and architectures are designed Learn best practices in data security, access control, and responsible AI usage Develop practical experience contributing to production-grade data/AI solutions in a business context Gain hands-on experience in building and managing end-to-end data pipelines Develop strong understanding of data modeling, data quality checks, and transformation techniques Become proficient in working with modern data stack tools (e.g., SQL, Python, cloud data platforms like AWS/Snowflake)

JOB REQUIREMENTS

1. Educational Background & Technical Foundations Pursuing a degree in Computer Science, Data Science, Engineering, or a related field Strong fundamentals in programming (preferably Python) and SQL Basic understanding of data structures, algorithms, and software engineering principles 2. Data & AI Knowledge Familiarity with data processing concepts (ETL/ELT, data modeling, data cleaning) Exposure to machine learning fundamentals (e.g., supervised/unsupervised learning, model evaluation) Experience with common data/ML libraries (e.g., Pandas, NumPy, scikit-learn) is a plus 3. Tools & Platform Exposure Exposure to cloud platforms (e.g., AWS, Azure, or GCP) and modern data ecosystems is advantageous Familiarity with databases (SQL/NoSQL) and data warehousing concepts (e.g., Snowflake, BigQuery, Databricks) 4. Problem-Solving & Mindset Strong analytical thinking and problem-solving skills Ability to break down complex problems into structured solutions Eagerness to learn and adapt in a fast-paced, technology-driven environment 5. Communication & Collaboration Good communication skills, with the ability to explain technical concepts clearly Team player with a proactive and ownership-driven attitude Ability to work with cross-functional teams (analytics, business stakeholders)

BUSINESS SEGMENT

Corporate

PLATFORM

Operating Division