AZURE ML ops Engineer

Role: AZURE ML ops Engineer
Location: Atlanta, GA
#Role is on-site, Must relocate
Must w2 Role

• Design and implement cloud solutions, build MLOps on cloud (AWS, Azure, or GCP)
• Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Circle CI, Airflow or similar tools
• Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality
• Data science models testing, validation and tests automation
• Communicate with a team of data scientists, data engineers and architect, document the processes

Required Qualifications:

• Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure or GCP)
• Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift
• Programming languages like Python, Go, Ruby or Bash, good understanding of Linux, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc.
• Ability to understand tools used by data scientist and experience with software development and test automation
• Fluent in English, good communication skills and ability to work in a team

Desired Qualifications:

• Bachelor’s degree in Computer Science or Software Engineering
• Experience in using AWS, MS Azure or GCP services.
• Good to have any associate Cloud Certification