Cloud Machine Learning Engineer

Overview

We are seeking a Cloud Machine Learning Engineer with hands-on experience in building, deploying, and managing ML solutions using Amazon Sage Maker and Google Cloud Platform (GCP). This role will focus on designing scalable machine learning pipelines, optimizing model performance, and supporting production-grade AI systems in a cloud-native environment.

Salary: 120k to 150k + bonus

• Design, build, train, and deploy machine learning models using Amazon Sage Maker.
• Develop and manage end-to-end ML pipelines in AWS and/or GCP environments.
• Implement data preprocessing, feature engineering, and model tuning workflows.
• Deploy and monitor models in production using cloud-native services.
• Collaborate with data engineers, Dev Ops, and application teams to integrate ML solutions.
• Optimize cloud infrastructure for performance, scalability, and cost efficiency.
• Ensure security, compliance, and best practices across cloud environments.

• Strong experience with Amazon Sage Maker for model development and deployment.
• Hands-on experience with Google Cloud Platform (GCP).
• Solid understanding of machine learning concepts and frameworks (e.g., Tensor Flow, PyTorch, Scikit-learn).
• Experience with Python and data processing tools.
• Knowledge of cloud networking, IAM, and infrastructure design.
• Experience with CI/CD and MLOps practices.

• Experience with containerization (Docker, Kubernetes).
• Familiarity with GCP ML tools such as Vertex AI.
• Exposure to data engineering tools and large-scale distributed systems.
• AWS and/or GCP certifications.