Job Description

Model Development & Training: Develop and train machine learning models, specifically in the domain of computer vision (e.g., object detection, image classification, segmentation). Optimize model performance by tuning hyperparameters and improving training pipelines. Data Preparation & Processing: Collect, clean, and preprocess image and video datasets for training models. Implement data augmentation and synthetic data generation techniques. Model Evaluation & Analysis: Evaluate model performance using appropriate metrics (e.g., precision, recall, F1-score). Perform error analysis to identify model weaknesses and suggest improvements. Model Deployment & Integration: Assist in deploying trained models into production environments. Work with software engineers to integrate computer vision models into applications or services. Research & Innovation: Stay updated on the latest trends and advancements in computer vision and machine learning. Experiment with state-of-the-art techniques such as transfer learning, self-supervised learning, and GANs. Role & responsibilities Preferred candidate profile Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). Familiarity with computer vision libraries (e.g., OpenCV, scikit-image). Understanding of machine learning concepts, including supervised and unsupervised learning. Knowledge of deep learning architectures (e.g., CNNs, RNNs, Transformers).