ML Ops Engineer

January 15, 2023

Job Description

  • 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.
    Required Qualifications:
    • 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.
    Desired Qualifications:
    • Bachelor’s degree in Computer Science or Software Engineering
    • Experience in using GCP services.
    • Good to have Google Cloud Certification