The responsibilities associated with this position include:

Review the deployment, monitoring, and maintenance aspects of machine learning related initiatives

• Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models.
• Collaborate with data scientists, data engineers, and domain experts to understand model requirements and optimize deployment processes.
• Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability.
• Implement best practices for version control, model reproducibility and governance.
• Optimize machine learning pipelines for scalability, efficiency and cost- effectiveness.
• Troubleshoot and resolve issues related to model deployment and performance.
• Ensure compliance with security and data privacy standards in all MLOps activities.
• Keep up-to-date with the latest MLOps tools, technologies and trends.
• Provide support and guidance to other team members on MLOps practices.

Other Duties

• Perform similar duties as he/she deems fit for the proper execution of his/her duties and duties as delegated by the immediate superior.

Requirements:

Skills:

• Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning services.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Knowledge of CI/CD pipelines, automation tools and version control systems like Git.
• Strong problem-solving skills and ability to troubleshoot complex issues.
• Excellent communication and presentation skills.

Experience:

• At least 3 years of working experience in an MLOps-related role.
• Proven and successful experience in deploying, monitoring, and maintaining machine learning models, from conceptual design to implementation.

Education:

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or any other related quantitative field