Lead ML Engineer (Europe-based/Remote)
SwordRemote
Full Time
Posted November 21, 2025
Not Specified
Remote
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Application opens on company website
Job Description
The Lead ML Engineer will develop and implement advanced AI and machine learning solutions to support personalized clinical care, including building end-to-end AI treatment management systems and engaging in prompt engineering, model fine-tuning, and workflow automation to enhance healthcare accessibility and quality.
Key Responsibilities
- Develop and implement AI and ML solutions for personalized clinical care.
- Build and maintain end-to-end AI treatment management systems.
- Design and optimize AI components such as prompt engineering, RAG implementations, and model fine-tuning.
- Create and improve agentic workflows for AI-driven patient engagement and clinical guidance.
- Leverage generative AI and classical machine learning techniques based on project requirements.
Requirements
- Experience developing AI and ML solutions that power personalized clinical care at scale.
- Proficiency in end-to-end AI treatment management systems, including handling complete care pathways from initial assessment through intervention selection and progress monitoring across various therapeutic domains.
- Experience building and deploying AI systems such as prompt engineering, RAG implementations, model fine-tuning, and agentic workflows.
- Ability to leverage both generative AI and classical machine learning depending on the problem requirements.
- Strong programming skills in relevant languages and frameworks used in AI/ML development (e.g., Python, TensorFlow, PyTorch).
- Experience working on projects involving AI dialogue systems or conversational agents, such as AI Care Specialists engaging in ongoing dialogue with patients.
- Demonstrated ability to work remotely from Europe-based locations.
- Educational background in Computer Science, Data Science, Machine Learning, or a related field, with a preference for advanced degrees (Master’s or PhD).
- Experience working in healthcare or clinical environments is preferred but not explicitly mandatory.
- Ability to contribute to delivering digital care that improves clinical quality and accessibility.
- Understanding of compliance with applicable Federal and State civil rights laws and non-discrimination policies (implied as a requirement for working in healthcare-related AI solutions).
Benefits & Perks
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