Machine Learning Engineer

ML Ops Engineer

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Hybrid

Full Time

Position Summary:

The MLOps Engineer is responsible for ensuring the smooth deployment, automation, and monitoring of AI models in production environments. This role requires expertise in DevOps practices, cloud computing, and AI model deployment. The MLOps Engineer will collaborate with AI Engineers and Data Scientists to build and maintain robust AI pipelines.

Key Responsibilities:

• Design and implement CI/CD pipelines for AI model deployment.
• Automate the deployment and monitoring of AI models.
• Manage and maintain AI infrastructure on cloud platforms.
• Implement monitoring and logging solutions for AI applications.
• Troubleshoot and resolve issues related to AI model deployment and performance.
• Ensure the scalability and reliability of AI systems.
• Collaborate with AI Engineers and Data Scientists to optimize model deployment.
• Implement security best practices for AI systems.

Qualifications:

• Bachelor’s or master’s degree in computer science, Software Engineering, or a related field.
• Minimum of 3 years of experience in DevOps or MLOps.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
• Proficiency in scripting languages such as Python or Bash.
• Strong understanding of CI/CD pipelines and automation tools.