Full-time Posted June 03, 2026
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Job Description

Overview

As a Machine Learning Engineer , you will bridge the gap between data science prototypes and production-grade machine learning systems. You will be responsible for deploying, scaling, and monitoring machine learning models in a production environment, ensuring reliability, performance, and maintainability across enterprise use cases.

Responsibilities

What You’ll Do and How You’ll Succeed

  • Productionise ML models from Jupyter notebooks into scalable and reliable services.
  • Build feature engineering pipelines and feature stores for real-time and batch inference.
  • Implement model serving infrastructure, including REST APIs, batch scoring, and streaming inference.
  • Design and maintain CI/CD pipelines for ML models as part of MLOps practices.
  • Monitor model performance, detect drift, and trigger automated retraining where needed.
  • Optimise model inference for latency and cost through te...

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