AIML Software Engineer, AI for Science

GSK

19h • Hybrid

About The Position

At GSK, we are actively working on building a future in which state-of-the-art software, Artificial Intelligence (AI) and Machine Learning (ML) enable us to develop new therapies and personalized medicines that drive better outcomes for patients at reduced cost with fewer side effects. This ambitious mission requires scalable, cloud-native solutions at the forefront of Software Engineering, Cloud Infrastructure, Efficient Compute, Machine Learning and AI. If this excites you, we would love to chat. About the Role To strengthen our AI for Science (AI4S) team, we are looking for Software Engineers with a track record in developing production-grade, data-driven software solutions. You will drive the development of scalable cloud infrastructure and efficient compute solutions to support large-scale AI models and agentic systems — building robust, high-performance software that enables scientific research using modern cloud technologies and the vast biomedical data sources available at GSK. Team Culture The AI4S 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.

Requirements

• 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 software engineer.
• Demonstrated advanced programming expertise in Python and in developing and delivering robust, scalable software solutions.
• Experience with cloud platforms (AWS, GCP, Azure) and cloud-native architectures.
• Passion for software design and commitment to the development of reusable, scalable, and testable software components.
• Basic understanding of at least one major deep learning framework (PyTorch, JAX, TensorFlow).
• Knowledge of command-line tools and shell scripting.
• Knowledge of software engineering best practices, including continuous integration (CI) and continuous deployment (CD), containerization, and infrastructure as code.
• Strong problem-solving and debugging skills, and experience working in cluster settings or cloud-based environments.
• Fluency in English.

Nice To Haves

• Familiarity with machine learning principles and state-of-the-art modelling approaches.
• Experience in design, development and deployment of commercial cloud-native software and infrastructure.
• Experience building and deploying large-scale AI models and agentic systems in production environments.
• Experience architecting, developing, and deploying distributed training pipelines for large models with PyTorch or TensorFlow.
• Expertise in performance optimization, cost optimization, and efficient compute resource management in cloud environments.
• Contributions to relevant open-source projects.
• Knowledge or interest in disease biology, molecular biology and medicine.
• Experience working with biomedical data (e.g., genomics, transcriptomics, proteomics, electronic health records, clinical images).

Responsibilities

• Design and implement scalable infrastructure and software solutions to support large-scale AI models and agentic systems across the entire software development life cycle.
• Design and implement sophisticated machine learning and deep learning pipelines that can handle massive amounts of data with optimal resource utilization.
• Develop and maintain cloud-native architectures that enable seamless deployment and scaling of AI/ML workloads.
• Deliver robust, tested and high-performance code in an agile environment.
• Liaise with AI/ML engineers, data scientists, and domain experts to ensure fit-for-purpose infrastructure and data pipelines for cutting-edge scientific projects.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level