Machine Learning Engineer - Infrastructure and Operations

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Requirements:

• Possess a strong background in machine learning, computer science, or a related field.
• Have 5+ years of experience in building and deploying machine learning models in production environments.
• Demonstrate proficiency in cloud computing platforms such as AWS, GCP, or Azure.
• Have experience with containerization technologies like Docker and orchestration tools like Kubernetes.
• Exhibit strong problem-solving skills and the ability to troubleshoot complex technical issues.
• Possess excellent communication and collaboration skills to work effectively in a remote team environment.

Responsibilities:

• Architect and maintain robust and scalable machine learning infrastructure.
• Collaborate with data scientists and engineers to deploy and monitor machine learning models.
• Implement automated workflows for model training, validation, and deployment.
• Optimize and fine-tune the performance of machine learning systems.
• Ensure data security, privacy, and compliance within the machine learning infrastructure.
• Troubleshoot and resolve infrastructure-related issues.
• Contribute to the evaluation and adoption of new technologies and tools in the machine learning space.