DevOps Engineer with MLOps

About this kind of role

What a DevOps Engineer with MLOps usually does. The employer's own details are in the listing.

Typically does: A DevOps Engineer with MLOps expertise focuses on streamlining the machine learning lifecycle, from model development to deployment and monitoring. This involves automating and optimizing the infrastructure and processes needed to build, test, and release machine learning models reliably. They collaborate closely with data scientists, software engineers, and operations teams to ensure efficient model delivery and performance. Responsibilities often include building CI/CD pipelines specifically tailored for machine learning workflows.

Tools and skills: Proficiency in cloud platforms (AWS, Azure, GCP), containerization technologies (Docker, Kubernetes), CI/CD tools (Jenkins, GitLab CI), scripting languages (Python, Bash), and machine learning frameworks (TensorFlow, PyTorch) is generally expected.

Good fit for: Individuals with a strong background in both DevOps practices and machine learning principles, who enjoy problem-solving and automating complex systems, are likely to thrive in this role.