Machine Learning Engineer

About the job

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

Requirements

• Machine Learning
• Deep Learning
• Python
• TensorFlow
• PyTorch
• scikit-learn
• OpenCV

Qualifications

• Master's degree in Computer Science
• Master's degree in Machine Learning
• Master's degree in Data Science

Preferred Technologies

• Machine Learning
• Deep Learning
• Python
• TensorFlow
• PyTorch
• scikit-learn
• OpenCV