AI/ML Scientist/Research Fellow

5 days ago

India Narayana Nethralaya Foundation Full time US$ 90,000 - US$ 1,20,000 per year

Our team is dedicated to transforming patient outcomes by building advanced diagnostic tools and decision-support systems using cutting-edge machine learning and deep learning technologies. Our team collaborates with top-tier medical institutions and researchers to develop robust solutions for medical imaging, including radiology, pathology, and multimodal image analysis. Position Overview:We are seeking a talented and motivated Machine Learning Engineer with experience in medical imaging to join our growing AI team.

You will be responsible for designing, developing, and deploying machine learning models that analyze complex medical images, support diagnosis, and improve clinical workflows. Key Responsibilities:Develop and optimize deep learning models for tasks such as segmentation, classification, detection, and registration of medical images (fundus, OCT). Preprocess large-scale medical imaging datasets, including DICOM handling, annotation standardization, and augmentation.

Collaborate with clinical experts, data engineers, and software developers to build and validate robust AI pipelines. Conduct literature reviews to stay updated on the latest research in medical imaging AI.Evaluate model performance using clinically relevant metrics. Assist in the deployment of models into clinical environment, including cloud-based solutions.

Qualifications:Master's or Ph. D. in Computer Science, Biomedical Engineering, Electrical Engineering, or a related field.1+ years of experience in machine learning and computer vision preferred. Proficient in Python and ML frameworks such as TensorFlow, PyTorch. Experience with medical imaging libraries (e.g., MONAI, ITK, SimpleITK, NiBabel, DICOM libraries).

Strong understanding of convolutional neural networks (CNNs), transformers, and other deep learning architectures. Familiarity with image annotation tools and dataset versioning platforms (e.g., CVAT, Labelbox, DVC). Preferred Skills:Experience with multimodal data (text, EHR, genomics) integration.

Knowledge of medical imaging modalities and pathology workflows. Experience with MLOps and model deployment in cloud environments. How to Apply:Submit your resume, cover letter, and links to relevant projects (GitHub, publications, portfolio) to *******

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