MLOps Engineer

We are looking for a strong MLOps Engineer with proven experience in building and managing scalable ML infrastructure. The ideal candidate will have hands-on expertise in Kubernetes, model deployment, Docker, Jenkins, and monitoring tools like :

• Design, build, and maintain MLOps pipelines to automate model training, validation, deployment, and monitoring.
• Containerize ML applications using Docker and manage deployments via Kubernetes.
• Integrate CI / CD pipelines using Jenkins for continuous delivery of ML models.
• Monitor and optimize the performance of models in production using tools like Prometheus.
• Collaborate with Data Scientists and DevOps teams to ensure smooth deployment and scaling of ML models.

Requirements :

Nice to Have :

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