Internship - AI Image Processing & Modelling

Infineon Technologies AG; Singapore; On-site; SGD 6,696 - 13,392; Part time

Job summary

Infineon Technologies AG offers an internship where you will expand Deep Learning AI models for image segmentation, classification and quantification using real production data. You will curate and expand image datasets, perform image labeling, and develop augmentation pipelines to improve diversity and model robustness.

You will gain hands-on experience across the AI development lifecycle, including training, validation, deployment, and end-to-end model development for engineering use cases,

Qualifications

• Pursuing a Bachelor's degree in a technical field with interest in data science, ML and AI.
• Familiarity with AI/ML model lifecycle: data prep, model training, validation, deployment, labeling, and optimization.
• Solid knowledge of Computer Vision and Image Processing concepts.
• Proficiency in Python and libraries such as OpenCV, PyTorch, and TensorFlow.

Responsibilities

• Expand Deep Learning AI models for Image Segmentation, Classification, and Quantification using production data.
• Expand, curate, and maintain image datasets for model training and validation.
• Perform image annotation and data labelling to support supervised learning workflows.
• Develop image synthesis and augmentation pipelines to improve dataset diversity.
• Evaluate model performance with appropriate metrics; benchmark and optimise inference efficiency.

Skills

Python

OpenCV

PyTorch

TensorFlow

Computer Vision

Image Processing

Data Science

Machine Learning

AI lifecycle

Education

Bachelor's degree (ongoing) in Computer Engineering/Data Science/Computer Science/Artificial Intelligence/Electrical & Electronic Engineering

Tools

OpenCV

PyTorch

TensorFlow

Job description

The student will be responsible for expanding AI models, building image datasets, and improving model performance through testing and optimisation activities.

Key Responsibilities

• Deep Learning Model Expansion: Support the expansion of Deep Learning AI models for Image Segmentation, Classification, and Quantification use cases with the latest production data.
• Deep Learning Dataset Expansion: Expand, curate, and maintain image datasets for model training and validation.
• Data Labelling: Perform image annotation and data labelling to support supervised learning workflows.
• Image Augmentation: Develop image synthesis and augmentation pipelines to improve dataset diversity with newer data.
• Model Testing: Evaluate model performance using appropriate metrics and validation methodologies; perform model testing, benchmarking, and optimisation to improve accuracy, reliability, and inference efficiency.

Internship Learning Outcomes

• Applied Deep Learning: Gain hands‑on experience building and optimising AI Computer Vision solutions for real industrial applications.
• Model Development End‑to‑End: Gain exposure to the full AI development lifecycle and application of deep learning in Engineering use cases.
• Real World Use Cases: Contribute to impactful digitalisation initiatives and strengthen your portfolio in AI and Data Science.

Qualifications and Skills

• Educational Background & Discipline: Currently pursuing a Bachelor's degree in Computer Engineering, Data Science, Computer Science, Artificial Intelligence, Electrical & Electronic Engineering, or a related technical discipline with strong aptitude and interest in Data Science, Machine Learning, and Artificial Intelligence.
• AI Proficiency: Familiarity with the AI/ML model development lifecycle, including data preparation, model training, validation, deployment, dataset annotation, image labelling techniques, and optimisation.
• Image Processing Skillset: Solid knowledge of Computer Vision and Image Processing concepts.
• Programming Proficiency: Proficiency in Python programming with familiarity in popular image processing and AI libraries such as OpenCV, PyTorch, and TensorFlow.
• AI Model Exposure: Exposure to Deep Learning architectures such as CNNs, U‑Net, EfficientNet, or related Computer Vision models and image use cases including classification, segmentation, and detection.
• Image Augmentation Understanding: Knowledge of data augmentation, synthetic data generation, or Generative AI techniques is a plus.

Contact: Hillary Woo

We embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to give all applicants and employees equal opportunities.

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