We’re looking to set the standard for a world-class, self-service, secure, and scalable MLOps platform that enables rapid experimentation and safe production deployment of ML and Generative AI models
Job Summary
We’re looking to set the standard for a world-class, self-service, secure, and scalable MLOps platform that enables rapid experimentation and safe production deployment of ML and Generative AI models.
As a Senior MLOps Engineer, you will apply modern engineering and MLOps practices to operationalise machine learning and Large Language Models (LLMs) at scale.
The role provides a strong opportunity to contribute to AI platform uplift, cloud adoption, and enterprise-grade ML enablement on AWS.
Matching Summary
We’re looking to set the standard for a world-class, self-service, secure, and scalable MLOps platform that enables rapid experimentation and safe production deployment of ML and Generative AI models.
Skills & Requirements
Must-have
MLOps platform
machine learning
automation
cloud-native AI solutions
AWS SageMaker
Python
CI/CD pipelines
monitoring and observability
Nice-to-have
Generative AI workloads
LLM platforms
enterprise-grade ML enablement
structured, engineering-led approach
Key Requirements
Hands-on experience operationalising machine learning models in a cloud environment (AWS preferred)
Strong experience with Python
Familiarity with SQL
Comfortable working in regulated, large-scale enterprise environments
Experience with Infrastructure as Code (CloudFormation or Terraform)
Experience with Docker and containerised ML workload