Skills & Requirements
MLOps engineer need to have an understanding of machine learning and software development.
Experience with python & SQL & Linux
Experience implementing solutions on cloud provider (AWS, Azure, or GCP)
Experience with Docker and Kubernetes
Ability to build MLOps pipelines
Knowledge of frameworks such as , PyTorch,
Experience with software development
Ability to understand tools used by the Data Scientists
Here are some non-technical skills required to become an MLOps engineer:
Strong communication skills – you need to be able to communicate with the Data Science team to understand the frameworks and types of models built.
Teamwork – As an MLOps engineer, your team would have people from many different backgrounds. Some of them might have more data science knowledge, while some might come from a software development background with little machine learning knowledge. You need to work with individuals with diverse skill sets and play on their strengths to develop a scalable application.
Business acumen – Ability to understand business issues.