Overview

Role Title:

ML Data EngineerCompany:

Experis UKRole Description:

We are seeking a highly capable Data and ML Engineer with strong experience in AWS-based machine learning pipelines, MLOps, and cloud-native deployment. This role focuses on building scalable data workflows, deploying ML models, and managing the full AI lifecycle in production environments.Start Date:

ASAPEnd Date:

End of Year (EOY)Location:

Knutsford (Hybrid)Rate:

£410 per day via Umbrella

Responsibilities

Build and maintain robust data pipelines and ML workflows on AWS

Develop and deploy machine learning models using SageMaker and MLOps tools

Implement CI/CD pipelines for automated testing and deployment

Create lightweight front-end interfaces for model interaction and visualization

Monitor model performance and ensure reliability in production environments

Collaborate with data scientists and engineers to streamline the AI lifecycle

Key Skills and Qualifications

AWS Data Engineering: ECS, SageMaker, cloud-native data pipelines

ML Engineering and MLOps: MLflow, Airflow, Docker, Kubernetes

CI/CD and DevOps: GitLab, Jenkins, automated deployment workflows

AI Lifecycle Management: Model training, deployment, monitoring

Front-End Development basics: HTML, Streamlit, Flask (for lightweight dashboards and interfaces)

Cloud Model Deployment: Experience deploying and monitoring models in AWS

Programming and Big Data: Python, PySpark, familiarity with big data ecosystems

RESTful APIs: Integration of backend services and model endpoints

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