The Lead ML Engineer will develop and oversee AI and machine learning solutions for personalized clinical care, including end-to-end treatment management systems and AI Care Specialists, to improve healthcare accessibility and quality across various therapeutic domains.
Key Responsibilities
Develop and implement AI and ML solutions for personalized clinical care.
Design and build end-to-end AI treatment management systems covering assessment, intervention, and monitoring.
Build and refine AI components such as prompt engineering, RAG implementations, and model fine-tuning.
Create and optimize agentic workflows for AI-driven patient engagement and clinical guidance.
Leverage generative AI and classical machine learning techniques based on project requirements.
Requirements
Proven experience in developing and deploying machine learning and AI solutions, including experience with end-to-end AI treatment management systems, prompt engineering, RAG implementations, model fine-tuning, and agentic workflows.
Strong knowledge and practical experience in leveraging both generative AI and classical machine learning techniques depending on the problem requirements.
Experience working on AI solutions that handle complete care pathways, including initial assessment, intervention selection, and progress monitoring across various therapeutic domains.
Ability to develop AI and ML models that contribute to delivering digital care with high clinical quality and accessibility.
Demonstrated experience in building AI systems that engage in ongoing dialogue with patients and provide clinical guidance throughout recovery journeys.
Excellent understanding of the full AI stack, including prompt engineering, model fine-tuning, and implementation of agentic workflows.
Proven ability to work remotely and collaborate effectively within a Europe-based team environment.
Educational background in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a related technical field (specific degree requirements not explicitly stated but implied by the technical nature of the role).
Experience working in healthcare or clinical environments, with an understanding of therapeutic domains and patient engagement (implied by the nature of the AI care solutions).