MLOps Engineer

Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models. Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes. Automate the training, testing and deployment processes for machine learning models. 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.

Bachelor's degree in computer science, Data Science or a related field. 3-10 years of experience in MLOps, DevOps or a related field. Strong understanding of machine learning principles and model lifecycle management.