About the Role
At GSK, we are leveraging Artificial Intelligence (AI) and Machine Learning (ML) to innovate in the development of new therapies and personalized drugs, aiming for improved patient outcomes at reduced costs and with fewer side effects. Given the critical safety and ethical implications of the datasets and algorithms utilized throughout the drug development process, GSK has a dedicated team focused on the responsible application of AI in healthcare.
We are seeking ML engineers or data scientists with a proven track record in successfully applying state-of-the-art Responsible AI methods to real-world datasets. Ideal candidates will possess exceptional ML engineering and data science skills, coupled with a strong interest in the ethical and safety aspects of AI usage in drug discovery and clinical settings.
The Responsible AI team operates on principles of ownership, accountability, continuous development, and collaboration. We are committed to fostering a supportive and engaging work environment and actively encourage applications from individuals with diverse and underrepresented backgrounds and perspectives.
In this role you will
- Apply state-of-the-art Responsible AI methods to challenges in drug discovery and complex biomedical datasets.
- Support various teams across AIML and GSK in establishing ethical ML pipelines and software products.
- Contribute to ML research focused on the responsible use of AI in drug discovery and clinical applications.
- Collaborate closely with research scientists, senior leaders, and AI/ML engineers on the implementation of GSK’s responsible AI strategy.
Qualifications & Skills
Required Skills:
- A degree in a quantitative or engineering discipline (e.g., computer science, computational biology, bioinformatics, engineering); OR equivalent professional experience as an ML engineer or data scientist.
- Demonstrated programming expertise in Python and experience with diverse 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.
- Eagerness to learn rapidly in new domains and to develop ML and software engineering skills.
- Proactive communication and problem-solving abilities, along with a proven capacity to collaborate effectively with colleagues of varying backgrounds and seniority levels.
Preferred Qualifications & Skills:
- 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.