Deep Learning Engineer

As a Deep Learning Engineer at SeaportAI, you will be responsible for utilizing your expertise in deep learning frameworks, programming, model development, healthcare data handling, MLOps basics, and problem-solving mindset to contribute towards building innovative solutions in the healthcare industry. **Key Responsibilities:** - Design and train deep learning models specifically tailored for medical imaging, diagnostics, and predictive healthcare analytics. - Collaborate effectively with clinicians, product teams, and data scientists to convert complex healthcare challenges into actionable AI solutions. - Handle and analyze real-world healthcare data such as images, time-series data, and Electronic Health Records (EHR) while ensuring compliance with regulatory standards like HIPAA/GDPR. - Participate in the development and optimization of model deployment pipelines to enhance performance in production environments. **Qualifications Required:** - Proficiency in Deep Learning Frameworks: You should be well-versed in PyTorch or TensorFlow. - Strong Programming Skills: Demonstrated experience in Python along with proficiency in NumPy, Pandas, and scikit-learn. - Experience in Model Development: Familiarity with Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), transformers, and self-supervised learning techniques. - Healthcare Data Handling: Exposure to medical images like DICOM, tabular EHR data, or time-series signals. - Understanding of MLOps Basics: Knowledge of model versioning, deployment tools such as ONNX and Docker, as well as performance monitoring. - Problem-Solving Mindset: Ability to create practical solutions in challenging, noisy data environments. - Bonus Skills: Any familiarity with medical standards like ICD codes, HL7, or participation in Kaggle/healthcare AI competitions would be advantageous. Please send your resume to info@seaportAI.com to apply for this exciting opportunity.,