About the Role
About the Role We’re looking for an MLOps Engineer to help scale machine learning from experimentation to production. You’ll work closely with Data Scientists, Software Engineers, and Product teams to build robust, automated, and secure ML infrastructure that supports model deployment, monitoring, and lifecycle management.
This is an exciting opportunity to shape best practices in CI/CD for ML, reproducibility, and cloud-native model serving within a growing, data-driven organisation based in Cambridge.
Key Responsibilities
Design, build, and maintain scalable ML pipelines (training, validation, deployment, monitoring)
Productionise machine learning models and ensure reliability, performance, and observability
Implement CI/CD workflows for ML using modern DevOps tooling
Manage containerised workloads (Docker/Kubernetes) in cloud environments (AWS/GCP/Azure)
Monitor model performance, drift, and data quality in production
Collaborate with Data Science teams...
This is an exciting opportunity to shape best practices in CI/CD for ML, reproducibility, and cloud-native model serving within a growing, data-driven organisation based in Cambridge.
Key Responsibilities
Design, build, and maintain scalable ML pipelines (training, validation, deployment, monitoring)
Productionise machine learning models and ensure reliability, performance, and observability
Implement CI/CD workflows for ML using modern DevOps tooling
Manage containerised workloads (Docker/Kubernetes) in cloud environments (AWS/GCP/Azure)
Monitor model performance, drift, and data quality in production
Collaborate with Data Science teams...
Ready to Apply?
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