How to Upgrade from DevOps Engineer to Highly Paid MLOps Engineer

How to Upgrade from DevOps Engineer to Highly Paid MLOps Engineer:
If you are a devops engineer and working in this role for more than three years then you can easily switch to highly paid mlops engineer and double your salary. As you are already aware of devops practices, tools and techniques to achieve software deployment in production efficiently and reliably. So with little effort and learning few extra techniques which I will be talking in next paragraphs, you can simply become the mlops engineer where you start deploying machine learning models in production. You might already be doing the same thing still your role says you are a devops and you are paid less. So this is the time to wake up and demand the right salary.
MLOps (Machine Learning Operations) engineers play a crucial role in deploying, managing, and optimizing machine learning models in production. Their responsibilities involve collaboration with data scientists, software developers, and IT operations to ensure the seamless integration of machine learning models into operational systems.
the add-on skills to become mlops engineer is to understand the machine learning lifecycle from pipeline orchestration point of view. It is not like that as an MLOps engineer you need to train the model, that is the job of a data scientist, all coding related part needed at each step of machine learning lifecycle will be done by either data scientists or data engineers, mlops main responsibility is to integrate every piece of code in a workflow or pipeline and setup a CI/CD pipeline for efficient and reliable model deployment in production.
watch the complete video to know more in details about the switch from devops to mlops.
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