AI Engineer - Clinical Development

Salary range: €100k - €125k

Meaningful equity

Relocation budget

Company Description we are focused on empowering the teams behind clinical trials by building the AI workspace for clinical development. The platform is designed to blend human expertise with machine precision, helping teams move from protocol to first patient in more quickly and with greater alignment. We emphasize on quality and compliance, ensuring that accelerated workflows do not compromise regulatory standards. We collaborate with leading biotechs, contract research organizations, and research institutions, and is backed by experienced operators in life sciences and AI, offering team members the opportunity to work at the intersection of healthcare and advanced technology.

Role Description You will work on-site (Hybrid) in Barcelona in a full-time capacity, developing and deploying AI solutions that power Cori Clinical’s workspace for clinical development. Day-to-day responsibilities include designing and training machine learning models, particularly in pattern recognition and neural networks, to support clinical trial workflows and decision-making. The role involves collaborating with product, clinical, and engineering teams to translate domain requirements into robust software systems and AI features. The AI Engineer will also optimize and maintain existing models, implement NLP components, ensure data quality and integrity, and contribute to scalable, secure software architectures that meet compliance standards. Regular code reviews, documentation, and participation in cross-functional planning are essential aspects of this position.

Qualifications

• Strong foundation in Computer Science and Software Development, including experience with modern programming languages, data structures, algorithms, and software engineering best practices.
• Demonstrated skills in Pattern Recognition and Neural Networks, with experience building, training, and evaluating machine learning models for real-world applications.

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• Hands-on experience with Natural Language Processing (NLP), such as text classification, entity extraction, and document understanding, preferably in complex or regulated domains.
• Familiarity with machine learning frameworks and tools and experience working with cloud or distributed computing environments.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience.
• Ability to collaborate effectively in cross-functional teams, communicate technical concepts clearly, and contribute to a respectful, inclusive work environment.
• Experience in life sciences, healthcare, or clinical research technology is beneficial, as is knowledge of data privacy, security, and compliance considerations.