Machine Learning Specialist

Company Description MediLoop is building core data infrastructure to power the future of healthcare in Uganda through a comprehensive, AI-enabled platform. The company provides a centralized, secure, and interoperable health record system designed to improve patient outcomes and streamline clinical workflows. MediLoop integrates health data from existing healthcare applications, wearables, and EHR systems into a unified, standardized repository. By leveraging AI-powered data processing, the organization aims to unlock the full potential of medical data and drive digital health innovation. Its vision is a connected, personalized health journey for every citizen, positioning Uganda as a leader in digital health. Role Description This is a full-time, on-site Machine Learning Specialist role based in Kampala. The Machine Learning Specialist will design, develop, and deploy machine learning and deep learning models that power MediLoop’s unified health data platform. Day-to-day responsibilities include exploring and preprocessing complex healthcare datasets, selecting appropriate algorithms, training and validating models, and optimizing performance for real-world clinical workflows. The role also involves collaborating with software engineers and product teams to integrate models into production systems, ensuring reliability, scalability, and data security. The specialist will contribute to research and experimentation, document technical approaches, and support continuous improvement of MediLoop’s AI capabilities. Qualifications

Strong foundation in Computer Science, including data structures, algorithms, and software engineering principles. Demonstrated expertise in Machine Learning and Deep Learning, with experience building and deploying models in production environments. Proficiency in Statistics and applied mathematical methods for model evaluation, inference, and performance analysis. Ability to design and implement efficient Algorithms tailored to large-scale, heterogeneous healthcare data. Hands-on experience with Python or similar languages, and frameworks such as TensorFlow, PyTorch, or scikit-learn. Familiarity with data engineering concepts, SQL/NoSQL databases, and handling structured and unstructured data. Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience. Strong problem-solving skills, attention to detail, and ability to work cross-functionally in a multidisciplinary environment. Experience with healthcare or digital health data, privacy regulations, and secure data handling is an advantage.

<