The Role of a DevOps Engineer
In today's fast-paced tech landscape, a DevOps engineer is vital for bridging the gap between development and operations. They streamline workflows, automate processes, and ensure seamless collaboration across teams. By implementing continuous integration and continuous deployment (CI/CD) practices, they enhance software quality and delivery speed. Their expertise in cloud technologies, infrastructure as code, and monitoring tools empowers organizations to innovate rapidly while maintaining reliability. Ultimately, DevOps engineers drive efficiency and foster a culture of collaboration.
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An MLOps engineer automates and manages the ML lifecycle — from data pipelines to model deployment, monitoring, and retraining — to make machine learning scalable, reliable, and production-ready.
Key Responsibilities:
Build and manage ML pipelines (training → deployment → monitoring)Deploy models using containers (Docker) and orchestration (Kubernetes)
Set up CI/CD for ML systems
Ensure reproducibility, scalability, and monitoring of models in production
Collaborate with data scientists and DevOps teams
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