About Us

Headquartered in Singapore, SATS Ltd. is one of the world’s largest providers of air cargo handling services and Asia’s leading airline caterer. SATS Gateway Services provides airfreight and ground handling services including passenger services, ramp and baggage handling, aviation security services, aircraft cleaning and aviation laundry. SATS Food Solutions serves airlines and institutions, and operates central kitchens with large-scale food production and distribution capabilities for a wide range of cuisines.

SATS is present in the Asia-Pacific, the Americas, Europe, the Middle East and Africa, powering an interconnected world of trade, travel and taste. Following the acquisition of Worldwide Flight Services (WFS) in 2023, the combined SATS and WFS network operates over 225 stations in 27 countries. These cover trade routes responsible for more than 50% of global air cargo volume. SATS has been listed on the Singapore Exchange since May 2000. For more information, please visit www.sats.com.sg

Why Join Us

At SATS, people are our greatest asset and we build our success on the knowledge, expertise and performance of every contributor, by embracing diversity and uniqueness. As part of our holistic approach and commitment to embracing FAM (Fulfilling, Appreciated, Meaningful) in the workplace, we offer the runway to develop Fulfilling careers that foster your career growth, recognising and Appreciating the strength of talent and capabilities that we continue to build internally; and inspiring and encouraging each other to make Meaningful contributions in the work we do at SATS.

Key Responsibilities

About the Role

This is a hands-on internship for a student who wants real exposure to building and operating the platform that our production-grade AI/ML, GenAI, Simulation, and Search systems run on. You will work directly under the Lead AI/Platform Engineer, contributing to actual pipelines, infrastructure, and tooling used by the AI Centre of Excellence — not a side project. Expect to spend most of your time writing code, working with cloud infrastructure, and learning production engineering practices, with regular guidance and code review from the Lead.
This role suits a student pursuing Computer Science, Software Engineering, Data Science, or a related field who wants practical, applied experience in AI/ML/GenAI platform engineering before graduating.

Key Responsibilities
Platform Engineering Support (Hands-On)
•    Assist in building and testing components of ML/GenAI pipelines (batch & real-time) under the Lead's direction
•    Help build and maintain model-serving infrastructure (e.g. FastAPI-based microservices) for internal use cases
•    Support development of RAG pipelines and simple LLM orchestration workflows
•    Assist with maintaining vector database and embedding pipeline infrastructure
Cloud & Infrastructure
•    Learn and apply cloud infrastructure fundamentals (AWS, Azure, or GCP) — compute, storage, networking, IAM — under supervision
•    Write and update infrastructure-as-code scripts (Terraform or equivalent) for small, well-scoped tasks
•    Support CI/CD pipeline maintenance and testing for ML/GenAI workloads
MLOps & Documentation
•    Help monitor model performance and flag issues to the Lead
•    Write and maintain documentation for tools, pipelines, and runbooks
•    Assist with reproducing and triaging bugs in ML systems
Learning & Collaboration
•    Work closely with the Lead AI/Platform Engineer and Senior/Junior AI Engineers on day-to-day tasks
•    Participate in code reviews (as a reviewee) and architecture discussions to build engineering judgment
•    Explore and evaluate emerging GenAI tools and frameworks, and share findings with the team

Key Requirements

Key Requirements
•    Currently pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Mathematics, or a related field
•    Foundational programming skills in Python
•    Basic understanding of software engineering practices (version control, testing, debugging)
•    Genuine interest in AI/ML, GenAI, or cloud platform engineering
•    Strong willingness to learn, ask questions, and take direction from the Lead AI/Platform Engineer
•    Able to commit to the internship on a full-time basis for the agreed duration

Preferred Qualifications
•    Coursework or personal/academic projects involving machine learning, cloud computing, or web APIs (e.g. FastAPI, Flask)
•    Exposure to Docker, basic Kubernetes concepts, or any major cloud platform (AWS, Azure, GCP)
•    Familiarity with Git and collaborative development workflows
•    Interest in the aviation, logistics, or supply chain domain — Cargo Handling, Ground Handling, Ground Freight, or Food Solutions