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
Machine learning platforms
Automation
Cloud-native AI solutions
AWS SageMaker
Python programming
CI/CD pipelines for ML
Nice-to-have
Enterprise-grade ML enablement
Responsible AI practices
Structured engineering-led approach
Key Requirements
Hands-on experience operationalising ML models in cloud
Experience with Infrastructure as Code
Experience with Docker and containerised ML workload
Experience supporting LLM or Generative AI workloads