Overview

Senior Machine Learning Engineer role at GSK.

At GSK we see a world in which advanced applications of Machine Learning and AI will allow us to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized drugs, driving better outcomes at reduced cost with fewer side effects. It is an ambitious vision that will require the development of products and solutions at the cutting edge of Machine Learning and AI. If that excites you, we'd love to chat. The AI/ML team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we\'re motivated to make this a great place to work. Our leaders will be committed to your career and development from day one.

In this role you will work with foundational genomics models and multiomics datasets from patients and lab experiments to model aspects of RNA biology that will inform our understanding of the molecular mechanisms of diseases, drug response, and design of best-in-class drugs in a new and exciting therapeutic modality. Familiarity and experience with genomics and RNA biology is a plus, but not required.

Responsibilities

• Optimise, accelerate and solve problems in biological systems using literature-informed mathematical modelling
• Build AIML models which interface with existing GSK systems and continuously improve upon business-relevant metrics via model and code iteration
• Design code architecture to operationalize data ingestion and processing
• Aggressively test code against project specifications
• Act as a technical mentor for junior team members
• Frequently demo work and/or lessons learned for their team and/or for the organization

Qualifications & Skills

• Significant industry experience in machine learning engineering
• Graduate studies in Computer Science or Applied Mathematics, undergraduate studies in Computer Science and relevant graduate studies in the life sciences with a focus on AI/ML techniques, or undergraduate studies in Computer Science and equivalent work history
• Experienced in software engineering with advanced skills in Python
• Advanced level in PyTorch, TensorFlow, or other deep learning frameworks
• Breadth across the ML stack, and depth in at least one discipline
• Demonstrated success shipping products powered by machine learning

Preferred Qualifications

• PhD in Computer Science/Mathematics/Machine Learning
• Academic or industry experience in the biomedical sciences, especially genetics or molecular biology
• Understanding and application of best practices in machine learning, software engineering, and/or production deployment of ML services
• Understanding of modern ML architectures, platforms, and backend systems
• Mentality of commit early and often, metrics before models, and shipping high quality production code
• Track record of contributing to open-source projects

Closing Date

Closing Date for Applications: Wednesday 17th September 2025 (COB)

Application guidance

Please take a copy of the Job Description, as this will not be available post closure of the advert. When applying, use the cover letter or CV to describe how you meet the competencies for this role, as outlined in the job requirements above. The information you provide will be used to assess your application.

EEO and adjustments During the course of your application, you will be requested to complete voluntary information which will be used in monitoring the effectiveness of our equality and diversity policies. Your information will be treated as confidential and not used in any part of the selection process. If you require a reasonable adjustment to the application/selection process, contact 0808 234 4391. For adjustments-related inquiries only, otherwise see the UK Recruitment FAQ guide.

Why GSK? Uniting science, technology and talent to get ahead of disease together. GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration regardless of race, color, religion, sex, pregnancy, gender identity, sexual orientation, parental status, national origin, age, disability, genetic information, military service or any basis prohibited under law. We support an agile working culture where feasible.