AI for Science: Cloud-Native ML Infra Engineer

GSK; Greater London; On-site; GBP 110,000 - 150,000; Full time

Job summary

GSK in London is seeking a Software Engineer to join the AI for Science (AI4S) team. You will design, build and operate scalable cloud infrastructure and services that support AI models and agentic systems, ensuring reliability in production and tight integration with scientists and data sources.

You will work hands-on on cloud-native architectures, CI/CD, monitoring and model-serving infrastructure, collaborating with ML engineers to deliver robust, high-performance software for research and

Qualifications

• Degree in quantitative or engineering discipline or equivalent experience.
• Advanced programming in Python and FastAPI for scalable software solutions.
• Experience with cloud platforms (GCP, Azure) and cloud-native architectures.
• Understanding of major DL frameworks (PyTorch, TensorFlow, JAX).
• CI/CD, containerization and Infrastructure as Code practices.
• Experience with SQL databases and live system support.
• Fluency in English.

Responsibilities

• Design, build and operate scalable infrastructure and services for AI models and agentic systems across the SDLC.
• Own reliability with CI/CD, automated testing, monitoring and alerting, and incident response.
• Build and operate model-serving infrastructure exposing models in production.
• Develop cloud-native architectures enabling reliable deployment and scaling of AI/ML workloads.
• Deliver robust, high-performance code in an agile environment; collaborate with ML engineers.

Skills

Python programming

FastAPI

Cloud platforms (GCP/Azure)

CI/CD pipelines

Kubernetes

SQL databases

English fluency

Shell scripting

Observability

DL frameworks basics

Education

Degree in CS/Engineering

Tools

Google Cloud Platform (GCP)

Terraform

Docker

Job description

GSK in London is seeking a Software Engineer to join the AI for Science (AI4S) team. You will design, build and operate scalable cloud infrastructure and services that support AI models and agentic systems, ensuring reliability in production and tight integration with scientists and data sources.

You will work hands-on on cloud-native architectures, CI/CD, monitoring and model-serving infrastructure, collaborating with ML engineers to deliver robust, high-performance software for research and