Overview

At GSK we see a world in which advanced applications of Machine Learning and AI will allow us to develop novel therapies and respond to emerging or changing diseases with personalized drugs. We are looking for an accomplished Senior Machine Learning Engineer to help make this vision a reality. You will work with foundational genomics models and multiomics datasets to model aspects of RNA biology that inform the molecular mechanisms of diseases, drug response, and design of best-in-class drugs in a new therapeutic modality. Familiarity with genomics and RNA biology is a plus, but not required.

Competitive candidates will have a track record of shipping high performing machine learning powered products in production environments. They are accomplished ML engineers with breadth across ML methods and depth in at least one area, and experienced software engineers with a track record of shipping stable, tested, performant code and services in an agile environment. A senior engineer can translate poorly defined problems into clear objectives and execute to build high performing products or services, serving as a model for code quality, standards, and best practices and mentoring junior team members.

Strong candidates will have graduate studies in Computer Science, Applied Mathematics, or equivalent (or life sciences with a focus on ML techniques) and 3+ years of industry experience building ML powered tools. Educational or professional background in biological sciences is a plus but not necessary. The AI/ML team emphasizes ownership, accountability, continuous development, and collaboration. We hire for the long term and are committed to your career and development from day one.

Responsibilities

• Optimise, accelerate and solve problems in biological systems using literature-informed mathematical modelling
• Build ML/AI models which interface with existing GSK systems and continuously improve 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 the team and the organization

Qualifications & Skills

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

Preferred Qualifications

• PhD in Computer Science, Mathematics, or Machine Learning
• Academic or industry experience in biomedical sciences, especially genetics or molecular biology
• Understanding and application of best practices in ML, software engineering, and/or production deployment of ML services
• Understanding of modern ML architectures, platforms, and backend systems
• Commitment to shipping high quality production code and data-driven decision making
• Track record of contributing to open-source projects

Closing Date

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

Please take a copy of the Job Description, as this will not be available post closure of the advert. When applying, describe how you meet the competencies for this role in your cover letter and CV.

During the course of your application, voluntary information may be requested to monitor equality and diversity policies. Information will be treated as confidential. If you require adjustments to the application process, contact 0808 234 4391. The helpline hours are 8.30am to 12.00 noon Monday to Friday; hours may vary on bank holidays. If your enquiry does not relate to adjustments, please refer to the UK Recruitment FAQ guide via the provided link.

Important notices

GSK is an Equal Opportunity Employer. We are committed to an agile working culture and to providing reasonable adjustments where needed. See our precise contact channels for adjustments and further information in the advert.

GSK does not accept referrals from employment businesses/agencies unless authorized in writing. This notice includes information on compliance requirements and may reference US transparency regulations where applicable.