Senior Scientist – AI Agent Systems for Drug Development

At Johnson & Johnsonwe believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented treated and curedwhere treatments are smarter and less invasive andsolutions are our expertise in Innovative Medicine and MedTech we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow and profoundly impact health for more at

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Johnson & Johnson Innovative Medicine (J&J IM) is recruiting for the role of Senior Scientist AI Agent Systems for Drug Development. This position has a primary location of Barcelona Spain. The secondary location is Madrid. This is a hybrid role.

J&J IM develops treatments that improve the health and well-being of people worldwide. Research and development areas encompass oncology cardiovascular and retina disorders immunology and neuroscience. Our goal is to help people live longer and healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market from patients to practitioners and from clinics to hospitals. To learn more about J&J IM please visit Machine Intelligence (MI) team within Data Science and Digital Health (DSDH) AI/ML is looking for a mission-driven Scientist to help develop the future of autonomous AI in drug discovery and development. Youll work with Large Language Models (LLMs) and sophisticated data science techniques harnessing massive datasets spanning scientific literature omics and biomolecular knowledge. Your work will directly accelerate how we discover therapeutics and advance them to clinical trialsmaking reasoning agents faster more accurate and more reliable. Key focus areas include multimodal reasoning agent robustness and uncertainty agent memory architecture and agent motivation frameworks.

Key Responsibilities:

• Develop and optimize multimodal reasoning systems that integrate large-scale structured and unstructured data to derive actionable conclusions

• Build novel agent memory architectures to enable persistent knowledge retention and context-aware decision-making across extended discovery workflows

• Prototype and evaluate innovative approaches for uncertainty quantification and reliability assessment in AI-driven scientific reasoning

• Serve as a domain expert within the field by articulating to team members emerging approaches and methodologies within the AI/ML with a clear understanding of their practical applications

• Benchmark agent performance against human expert decisions and existing computational methods and demonstrate ability to publish results in leading journals and conferences

Required qualifications:

• A Ph.D. degree in AI/ML or related field (e.g. computer science machine learning data science applied mathematics statistics) with at least two (2) years working experience

• Knowledge in sophisticated mathematics areas such as Bayesian inference uncertainty quantification information theory causal inferencing graph neural networks etc.

• Proficiency with open-source agentic frameworks (e.g. LangGraph DSPy mem0 etc.) and deep learning frameworks (e.g. PyTorch Tensorflow etc.)

• Proficiency in one or more programming languages preferably Python

• Positive and motivated demeanor with the ability to work both independently and in a diverse multi-disciplinary team

Preferred (nice-to-have) qualifications:

• Understanding of drug discovery pipeline and familiarity with biological data types

• Experience in chemical engineering protein engineering or manufacturing-related fields

• Strong understanding of statistics and applicable methods to validate model performance

• Familiarity with cloud hosting solutions (ex. AWS and/or Azure)

Johnson & Johnson is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity age national origin and will not be discriminated against on the basis of disability.

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