GSK is revolutionizing healthcare through AI and ML applications in drug development and personalized medicine. The Responsible AI team focuses on ensuring the ethical and safe implementation of AI in healthcare solutions. As an AI/ML Engineer in the Responsible AI team, you'll be at the forefront of applying cutting-edge machine learning techniques to drug discovery and clinical applications while ensuring responsible AI practices.
The role combines technical expertise in ML engineering with a focus on ethical considerations in healthcare AI applications. You'll work with various datasets including genomics, electronic health records, and clinical images to deliver insights that drive better patient outcomes. The position offers opportunities to contribute to ML research while implementing practical solutions that align with GSK's responsible AI strategy.
The team culture emphasizes ownership, accountability, continuous development, and collaboration. GSK is committed to long-term career development and fostering an inclusive environment where diverse perspectives are valued. You'll work alongside research scientists and senior leaders, contributing to both technical implementations and strategic initiatives.
This position is ideal for candidates who combine strong technical ML skills with an interest in ethical AI applications in healthcare. You'll be part of a global biopharmaceutical company focused on uniting science, technology, and talent to advance disease treatment and prevention. GSK offers a supportive environment for professional growth, with opportunities to work on meaningful projects that impact global health outcomes.
The role requires expertise in Python programming, experience with deep learning frameworks, and the ability to work with complex datasets. You'll be expected to contribute to building ethical ML pipelines and software products while collaborating with cross-functional teams. The position offers the chance to work at the intersection of AI technology and healthcare, making a real difference in patient care while ensuring responsible AI practices.