Machine Learning Engineer

We are seeking a highly skilled Machine Learning Engineer to join a team focused exclusively on building and deploying machine learning models—not data science.

The ideal candidate will have hands-on experience with ML engineering, MLops, Amazon Sage Maker, and Python, and will be responsible for developing scalable ML pipelines and production-ready solutions.

Key Responsibilities

• Design, build, and deploy machine learning models in production environments.
• Develop and maintain ML pipelines using Amazon Sage Maker and other cloud-native tools.
• Implement MLops practices for model versioning, monitoring, and automation.
• Collaborate with software engineers and data engineers to integrate ML models into applications.
• Optimize model performance and scalability for real-time and batch inference.
• Ensure compliance with best practices in security, reliability, and maintainability.
• Write clean, efficient, and well-documented Python code for ML workflows.

• Strong hands-on experience with Amazon Sage Maker.
• Proficiency in Python for ML development and automation.
• Experience implementing MLops practices in production environments.
• Solid understanding of machine learning model lifecycle and deployment strategies.
• 5+ years of experience in machine learning engineering or related roles.
• Familiarity with cloud platforms (AWS preferred).

• Experience with containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes).
• Familiarity with CI/CD pipelines for ML workflows.
• Exposure to monitoring tools and model performance tracking.

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