Key Responsibilities

• Design, develop, and implement ML models for medical image recognition and analysis
• Fine-tune pre-trained deep learning models (CNNs, Vision Transformers) for diagnostic imaging tasks
• Conduct extensive model evaluation and validation using imaging datasets and clinical benchmarks
• Collaborate with healthcare professionals and domain experts to understand clinical requirements
• Optimise model performance, accuracy, and inference speed for production deployment
• Develop data pipelines and preprocessing workflows for large-scale imaging datasets
• Document methodologies, results, and create technical reports for stakeholders
• Stay updated with the latest research and advancements in diagnostic AI and medical Period : Immediate joiners or candidates who can join within 30 days Skills and Qualifications :
• Master's degree or higher in Computer Science, Machine Learning, Data Science, or related field
• 4+ years of hands on experience in machine learning and deep learning
• Proven experience with medical image recognition, diagnostic AI, or healthcare-related ML projects
• Strong proficiency in Python and popular ML frameworks (TensorFlow, PyTorch, scikit-learn)
• Experience with image processing libraries (OpenCV, Pillow, DICOM) and medical imaging formats
• Solid understanding of convolutional neural networks (CNNs) and transfer learning techniques
• Familiarity with model evaluation metrics for imaging tasks (sensitivity, specificity, AUC, F1-score)
• Strong problem-solving and analytical skills

(ref:hirist.tech)