Health AI Engineer

Design, build, and deploy AI solutions for healthcare-related use cases. Develop machine learning models for health data analysis, prediction, and decision support. Work with clinical, operational, or health-related datasets to extract useful insights. Build AI-powered tools such as chatbots, screening systems, recommendation engines, or diagnostic support systems. Collaborate with healthcare professionals, product teams, and software engineers to understand problems and create practical AI solutions. Clean, preprocess, and analyze structured and unstructured health data. Integrate AI models into web, mobile, or backend systems using APIs. Monitor model performance, accuracy, reliability, and safety after deployment. Ensure AI solutions follow ethical, privacy, and data protection standards. Document models, processes, experiments, and technical decisions clearly.

Strong background in AI, machine learning, data science, or software engineering. Experience working with Python and AI/ML libraries such as scikit-learn, TensorFlow, PyTorch, or similar tools. Understanding of healthcare data, medical workflows, or digital health systems is an advantage. Experience with data cleaning, feature engineering, model training, evaluation, and deployment. Ability to work with APIs, databases, and backend systems. Knowledge of natural language processing, computer vision, or predictive analytics is a plus. Familiarity with health data privacy, ethical AI, and responsible AI practices. Strong problem-solving and analytical thinking skills. Ability to communicate technical ideas clearly to both technical and non-technical teams. A portfolio, GitHub projects, or previous AI/health-tech projects is an advantage. • 2 years of experience required