Cloud-Native ML Engineer

1. Design scalable ML pipelines with cloud-native tools

2. Deploy & monitor ML models via Kubernetes, Docker, or serverless

3. Automate workflows using Kubeflow, Airflow, Vertex AI, or Sagemaker

4. Optimize inference & cost on AWS/GCP/Azure

5. Build CI/CD for ML services

6. Implement monitoring, logging & auto-scaling

Overview

• Industry - Machine Learning / ML / Artificial Intelligence / AI
• Functional Area - IT Robotics & Automation / IoT / Machine Learning
• Job Role - Software Developer IoT, Cloud, ML, Big Data Analytics
• Employment type - Full Time - Permanent
• Work Mode - Remote

Qualifications

• Any Graduate - Any Specialization
• Any Post Graduate - Any Specialization
• Any Doctorate - Any Specialization

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