We are looking for a skilled AWS MLOps Engineer to help deploy, automate, and manage production-grade machine learning solutions within our clients AWS environment.
Take the next step in your career now, scroll down to read the full role description and make your application.
This is a great opportunity for a MLOps Engineer to become a vital part on a new data team.
This is a hybrid role with the expectation to be in the London office 1-2 times per week.
Key Responsibilities Deploy ML models as real-time endpoints using Amazon SageMaker
* Build and manage batch inference pipelines
* Implement CI/CD workflows for ML using Git-based processes
* Containerize applications using Docker
* Monitor model performance, data drift, and system health using CloudWatch
* Automate data pipelines and feature workflows using Python & SQL
* Ensure secure access and governance using AWS IAM and best practices Core AWS Stack Amazon SageMaker | Amazon S3 | Amazon Redshift | AWS Lambda | Amazon CloudWatch | AWS IAM What We're Looking For ? Strong hands-on experience with AWS ML infrastructure ? Experience deploying and monitoring ML models in production ? Proficiency in Python and SQL ? Knowledge xxuwjjq of Docker and CI/CD pipelines ? Experience with Infrastructure-as-Code (CloudFormation preferred) This role focuses on transforming machine learning from experimentation into secure, scalable, production-ready systems .