Temukan Karir Impianmu

What You'll Be Doing 

• Data Annotation: Labeling images and videos for training our vision models (bounding boxes, segmentation, classification) 

• Model Testing: Running experiments, testing model performance, documenting results 

• Quality Checking: Reviewing model outputs, identifying edge cases and failure modes 

• Building & Experimentation: Contributing to building pipelines, trying new approaches, and improving existing systems 

• Documentation: Maintaining clear records of datasets, experiments, and findings 

Basic Requirements 

Educational Background 

Currently enrolled as a Bachelor's degree student in:  Computer Science, Informatics Engineering, Data Science, Electrical Engineering, Mathematics/Statistics, Or related technical fields 

• Minimum semester 5 or above (preferred) 

Technical Skills 

Must Have: 

Python Programming: Comfortable writing scripts, functions, and working with basic data structures, and OOP. 

Basic AI/ML Knowledge: Understanding fundamental concepts such as:  

• Supervised vs Unsupervised learning 

• Training, validation, and testing data 

• Basic idea of how neural networks work 

• What computer vision is and its applications 

Problem-solving mindset: Can debug code and figure out issues independently 

Good to Have (Plus Points): 

• Familiarity with computer vision concepts (image processing, object detection, image classification) 

• Experience with deep learning frameworks (TensorFlow, PyTorch, Keras) 

• Used Jupyter Notebooks or Google Colab for experiments 

• Basic understanding of image/video formats and processing 

• Knowledge of OpenCV or similar CV libraries 

• Basic Git/GitHub experience 

• Experience with data annotation tools (LabelImg, CVAT, etc.)