Engineer
Site Name: London The Stanley Building
Posted Date: May 14 2025 At GSK, we are using Artificial Intelligence (AI) and Machine Learning (ML) to develop new therapies and personalized drugs that drive better outcomes for patients at reduced cost with fewer side effects. Because the datasets we use and algorithms we build at each step of the drug development journey have safety and ethical implications for our patients, GSK has a dedicated team working on the responsible use of AI in healthcare. We are looking for ML engineers or data scientists that have a track record in successfully applying state-of-the-art Responsible AI methods to real-world datasets. In addition to outstanding ML engineering and data science skills, ideal candidates will demonstrate a keen interest in ethical and safety aspects of using AI in drug discovery and the clinic. The Responsible AI team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we are motivated to make this a great place to work. Our leaders will be committed to your career and development from day one. We strongly encourage applications from people with diverse and underrepresented backgrounds and perspectives. In this role you will- Apply state-of-the-art Responsible AI methods to problems in drug discovery and challenging biomedical datasets.
- Support different teams across AIML and GSK in building ethical ML pipelines and software products.
- Contribute to ML research on the responsible use of AI in drug discovery and clinical applications.
- Work closely with research scientists, senior leaders and AI/ML engineers on the implementation of GSK’s responsible AI strategy.
- A degree in a quantitative or engineering discipline (e.g., computer science, computational biology, bioinformatics, engineering, among others); OR equivalent work experience as a professional ML engineer or data scientist.
- Demonstrated programming expertise in Python and experience working with different types of complex and/or multi-modal datasets.
- Solid understanding of at least one major deep learning framework (PyTorch, TensorFlow).
- Knowledge of machine learning principles and state-of-the-art modelling approaches.
- Track record of research (e.g. via publications) in the field of Responsible AI.
- Keenness to learn fast in a new domain and to develop your ML and software engineering skills.
- Proactive communication and problem-solving, and a proven ability to collaborate with colleagues of various backgrounds and levels of seniority.
- Experience working with biomedical data (e.g., genomics, transcriptomics, proteomics, electronic health records, clinical images).
- Contributions to relevant open-source projects.
- A background or interest in drug discovery, biology, medicine or ethics.
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