Site Name: London The Stanley Building
Posted Date: Aug 27 2025
At GSK, we see a world where advanced applications of Machine Learning and AI empower us to drive groundbreaking solutions that further our mission of enabling everyone to do more, feel better, and live longer. This ambitious vision will rely on developing cutting-edge products and solutions in Machine Learning and AI.
Our team focuses on creating full-stack, AI-powered tools to support the most important question at the highest level: which drugs to develop and when. By leveraging data from across the organisation and beyond- from clinical trial readouts to external market analyses- we improve financial strategies and optimize decision-making. We are seeking accomplished AI Engineers to help us accelerate these efforts and bring more ambitious, patient-focused solutions to life. Strong candidates will have a track record in developing production grade software solutions and experience doing research at the edge of AI innovation.
Our AI/ML team operates on principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we’re committed to creating an excellent working environment. Our leaders are dedicated to your career growth and development from day one.

QUALIFICATIONS & SKILLS:

We are looking for professionals with these required skills to achieve our goals:

• A minimum of a master’s degree in computer science, applied maths, statistics, physics, engineering or other technical field
• Advanced programming expertise in Python and experience developing and delivering robust software solutions, including code testing
• Understanding and applying best practices in Machine Learning, with breadth across the ML pipeline
• Mentality to commit early and often, metrics before models, and shipping high quality production code
• Understanding of modern ML Architectures, Platforms, and backend systems, including PyTorch or TensorFlow
• Proven ability to solve complex problems using creative approaches, state-of-the-art tools, and best engineering practices
• Ability to work both autonomously and collaboratively on complex projects
• Experience shipping products powered by machine learning
• Experience in deploying AI/ML solutions with cloud computing Platforms, such as Azure

CLOSING DATE FOR APPLICATIONS: WEDNESDAY 10TH SEPTEMBER 2025 (COB)

Please take a copy of the Job Description, as this will not be available post closure of the advert.
When applying for this role, please use the ‘cover letter’ of the online application or your CV to describe how you meet the competencies for this role, as outlined in the job requirements above. The information that you have provided in your cover letter and CV will be used to assess your application.
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 will not be used in any part of the selection process. If you require a reasonable adjustment to the application / selection process to enable you to demonstrate your ability to perform the job requirements, please contact 0808 234 4391. This will help us to understand any modifications we may need to make to support you throughout our selection process.

• Optimise, accelerate and solve problems by applying literature review and mathematical modelling
• Design code architecture to operationalise data ingestion and algorithms
• Build models, services, and libraries that fulfil the stated API contract and metrics for a project
• Effectively iterate on model design, training process design, code abstractions, etc. to improve key metrics of the model, service, or library
• Aggressively test code to ensure the specification is met
• Proactively communicate problems, delays, and changes to project lead or senior engineers and ask for help
• Engage with code review and view it as a learning tool to improve engineering practice
• Commit code early and often, and seek feedback along the way when needed
• Frequently demo work and/or lessons learned for their team or for the organisation