AI Vision & Image Processing Internship

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

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,