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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.
Job Responsibility:
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
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 have:
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)
What we offer:
Competitive base salary
Annual bonus based on company performance
Flexible working options available for most roles
Learning and career development
Access to healthcare & wellbeing programmes
Employee recognition programmes
Health care and other insurance benefits (for employee and family)