MLOps involves managing the deep learning or production ML lifecycle, incorporating ML, DevOps, and data engineering processes. Responsibilities include designing and implementing cloud solutions, building MLOps on my client's cloud platform, orchestrating CI/CD pipelines, reviewing data science models, testing and automating processes. The role requires expertise in MLOps frameworks, Docker, Kubernetes, and proficiency in programming languages such as Python, Go or Bash. Effective communication and collaboration with a diverse team of data scientists and engineers are essential.
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