AIML Software Engineer, AI for Science

GSK is looking for a Software Engineer for their AI for Science team to design, build and operate scalable cloud infrastructure and services for AI models and agentic applications, ensuring reliable production performance in drug discovery.

• Design, build and operate scalable infrastructure and services that support our AI models and agentic systems across the entire software development life cycle.
• Own the reliability of what you build — set up CI/CD and release processes, automated testing, monitoring and alerting, and lead the response when things break.
• Build and operate the model-serving infrastructure that exposes our models in production with efficient use of compute.
• Develop and maintain cloud-native architectures that enable reliable deployment and scaling of AI/ML workloads.
• Deliver robust, tested and high-performance code in an agile environment, and work closely with ML engineers and domain experts to make the infrastructure fit for purpose.

• Degree in a quantitative or engineering discipline (e.g., computer science, computational biology, bioinformatics, engineering) OR equivalent work experience.
• Advanced programming expertise in Python.
• Experience developing and delivering robust, scalable software solutions using frameworks like FastAPI.
• Experience with cloud platforms (GCP, Azure) and cloud-native architectures.
• Passion for software design and commitment to 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 CI/CD, containerization, and infrastructure as code.
• Strong problem-solving and debugging skills, experience in cluster/cloud environments.
• Experience operating production services — monitoring, observability, alerting, and diagnosing issues in live systems.
• Experience designing and administering SQL databases — schema design, query performance, operational management.
• Hands-on experience with Google Cloud Platform (Cloud Run, GKE, Cloud Storage, Artifact Registry, Cloud SQL).
• Fluency in English.