AI Systems & Machine Learning Operations (MLOps) Engineer

About The Role

Design, deploy, and manage scalable AI platforms and MLOps pipelines, ensuring the performance, reliability, scalability, and security of AI systems throughout their lifecycle.

Key Responsibilities

• Design, deploy, and maintain scalable AI platforms and MLOps pipelines.
• Manage AI infrastructure, deployment, and CI/CD pipelines.
• Monitor AI systems and machine learning models to ensure performance, reliability, and availability.
• Ensure the scalability, security, and operational stability of AI platforms.
• Automate model deployment, monitoring, and lifecycle management.
• Collaborate with data scientists and software engineers to operate AI solutions.
• Troubleshoot and optimize AI infrastructure and production environments.
  
  

Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
• 3–8 years of relevant experience in AI systems engineering, MLOps, or machine learning platform engineering.
• Strong experience with Python, Docker, Kubernetes, and cloud platforms.
• Experience with CI/CD pipelines and machine learning frameworks.
• Experience managing AI infrastructure and deploying machine learning solutions.
  
  

Preferred Qualifications

• Experience with Azure ML, AWS SageMaker, or Vertex AI.
• Experience with Terraform or other Infrastructure as Code (IaC) tools.