aimlroles

[Keppel Internship Programme 2027] Intern, AI Platform (Jan - May 2027)

Keppel Open · verified Oct 22, 2026
Singapore Full-time Junior ML Platform & Ops

At a glance

Junior ML Platform & Ops role at Keppel. Singapore · full-time.

Pay not stated ML Platform & Ops salary

RoleML Platform & Ops
SeniorityJunior
LocationSingapore
EmploymentFull-time
PostedJul 28, 2026 · 2mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Turn AI and machine learning ideas into proof-of-value work, including technical plans for models and their deployment
  • Build solutions using existing architectures and deployment frameworks, following development standards for scale and repeatability
  • Design and improve data pipelines for local model training, validation and production, protecting data quality, provenance and privacy

What you bring

  • A bachelor's degree in computer science, machine learning, AI or another related quantitative field
  • A strong grasp of computing, machine learning and deep learning algorithms
  • Proficiency in Python and prompting, plus strong SQL knowledge
  • Knowledge of cloud platforms such as AWS for building scalable solutions

Who this fits

This internship suits someone seeking hands-on experience across an AI/ML project, from problem formulation and data acquisition through deployment, monitoring and user feedback. The placement runs from January to May 2027.

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: '1. Create Proof Of Value from ideation/ technical specifications for AI and machine learning models, including data pipelines, feature engineering, model architecture, and deployment strategies. 2. Building Solutions on top of existing architectures, deployment frameworks, and development standards for scalability and reproducibility. 3. Designing and optimizing end-to-end data pipelines for local model training, validation, and production, ensuring data quality, provenance, and privacy. Learning Outcomes: '1. Experience working on real-life AI and machine learning projects that directly impact the revenue & profit of a multi-national company. 2. Experience working in a multicultural team. 3. End-to-end understanding of implementing an AI/ML project, starting from problem formulation and data acquisition to model deployment, monitoring, and user feedback.

JOB REQUIREMENTS

Bachelor's degree in Computer Science, Machine Learning, AI, or a related quantitative field. Strong understanding of computing, machine learning and deep learning algorithms. Proficiency in Python, Prompting; strong knowledge of SQL. Knowledge of cloud platforms (e.g., AWS) for scalable solution development.

BUSINESS SEGMENT

Corporate

PLATFORM

Operating Division