- Key responsibilities:
- Design and implement cloud solutions, build MLOps on cloud (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.
- Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (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.
- Bachelor’s degree in Computer Science or Software Engineering
- Experience in using GCP services.
- Good to have Google Cloud Certification