Job Description
Job Title:
Intern, Data Science
Job Location:
Inflight Catering Centre 1
Job Description:
About Us
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Headquartered in Singapore, SATS Ltd. (SGX stock code: S58) 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
- Domain Flexibility: As an intern, you will have the unique opportunity to tailor your experience. Depending on your interests and career goals, you can choose to specialize deeply in either Computer Vision or Generative AI, or opt for a hybrid experience that allows you to contribute to and learn from both domains.
- Computer Vision (CV)
- Model Development: Assist in building, training, and optimizing computer vision models (e.g., object detection) for real-world operational use cases. This includes dataset preparation, evaluation, and iteration using modern CV metrics (e.g., precision, recall, mAP).
- Pipeline Engineering: Collaborate on developing end-to-end CV pipelines—from raw camera feeds to actionable outputs. Involve in image/frame pre-processing, inference optimization, and post-processing to support workflows like shipment/label detection and downstream system updates.
- Operational Readiness: Contribute to testing and deployment phases by assisting with User Acceptance Testing (UAT), conducting performance checks (latency, reliability), and documenting model behavior for seamless handover.
- Monitoring & Troubleshooting: Support post-deployment activities, including investigating model anomalies, monitoring performance drift, and managing model updates.
- Generative AI
- Data Extraction Workflows: Build and iterate on LLM-assisted workflows designed to convert unstructured data (e.g., emails, documents) into reliable, structured formats.
- Workflow Orchestration: Implement and enhance deterministic automation pipelines (e.g., email triggers, multi-step routing) using workflow services and function calling, ensuring robust human-in-the-loop validation.
- Framework Contribution: Contribute to the development of a reusable GenAI framework that enables multiple conversational and non-conversational use cases, focusing on centralized governance, prompt management, and cost optimization.
Key Requirements
- General Qualifications
- Currently pursuing an Undergraduate or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Information Systems, or a related quantitative discipline.
- Strong Python programming fundamentals
- Familiarity with version control (Git), debugging workflows, and writing clean, maintainable code.
- Soft Skills: Structured problem-solving mindset, clear communication skills, and the ability to collaborate effectively with cross-functional teams in an environment of iterative experimentation and ambiguity.
- Bonus: Cloud/edge computing awareness, including familiarity with deploying models, containerization (Docker), or working with cloud ML platforms (AWS/GCP/Azure).
- Computer Vision
- Academic coursework, projects, or prior internship experience in Computer Vision, particularly in object detection, tracking, or segmentation.
- Familiarity with common CV libraries and frameworks (e.g., OpenCV, PyTorch, TensorFlow).
- Understanding of dataset curation and annotation processes, including exposure to annotation tools and standard export formats (e.g., YOLO, COCO).
- Generative AI & NLP
- Understanding of unstructured text processing and techniques for structuring noisy inputs into reliable outputs.
- Exposure to Large Language Models (LLMs) and Generative AI concepts, including basic prompt engineering, evaluation frameworks, and API integration.
- Understanding of how GenAI components can be integrated into broader automation workflows (e.g., combining structured outputs from a model with LLM-based reasoning).