Overview:
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
Skills:
Azure,MLOP,Data Science,Kubeflow,DataRobot