Skill Sets Needed

• Deep Learning Frameworks: Proficient in PyTorch or TensorFlow
• Programming: Strong Python skills with experience in NumPy, Pandas, and scikit-learn
• Model Development: Experience with CNNs, RNNs, transformers, and self-supervised learning
• Healthcare Data Handling: Exposure to medical images (e.g., DICOM), tabular EHR, or time-series signals
• MLOps Basics: Knowledge of model versioning, deployment tools (e.g., ONNX,Docker), and performance monitoring
• Problem-Solving Mindset: Ability to build practical solutions in resource-constrained, noisy data environments
• Bonus: Familiarity with medical standards (e.g., ICD codes, HL7) or experience in Kaggle/healthcare AI competitions

Key Responsibilities

• Design and train deep learning models for medical imaging, diagnostics, and predictive healthcare analytics
• Collaborate with clinicians, product teams, and data scientists to translate healthcare problems into AI solutions
• Work with real-world healthcare data (images, time-series, EHR), ensuring regulatory compliance (e.g., HIPAA/GDPR)
• Contribute to model deployment pipelines, optimizing performance in production environments