MLOps Engineer - CI / CD Pipeline

Key Responsibilities :

• Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI / CD / CT) of ML models.
• Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability.
• Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production.
• Collaborate with data scientists to transition models from research and development into a production-ready state.
• Automate the retraining and redeployment of models to maintain accuracy and adapt to new data.
• Troubleshoot and resolve issues related to model deployment, performance, and infrastructure.
• Stay updated on the latest MLOps tools, technologies, and best Qualifications :
• 3+ years of professional experience in MLOps, DevOps, or a similar role.
• Strong proficiency in Python and experience with machine learning frameworks like TensorFlow or PyTorch.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and their respective ML services.
• Proven experience with containerization (Docker) and orchestration (Kubernetes).
• Familiarity with CI / CD tools and version control systems Qualifications :
• Experience with specific MLOps platforms like Kubeflow, MLflow, or SageMaker.
• Knowledge of data engineering and building data pipelines.
• A strong understanding of machine learning concepts and algorithms

(ref : hirist.tech)