Engineering Manager - MLOps

Typical duties and responsibilities : - 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. Required skills and experience : - 3-5 years of experience in MLOps, DevOps or a related field. - Bachelor's degree in Computer Science, Data Science or a related field. - Strong understanding of machine learning principles and model lifecycle management. - 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. - Experience with monitoring tools and practices for model performance in production. - Ability to work collaboratively in cross-functional teams. (ref:hirist.tech)

Location: in, IN

Posted Date: 4/18/2025