ML Ops Engineer

Skills:.

ML, GCP, ML Ops, Ci/CD, Airflow, Keras,

Role:ML Ops Engineer

Experience:6-9 Yrs

Location:Bangalore


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 architects, 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

Bachelors degree in Computer Science or Software Engineering

Experience in using GCP services.

Good to have any associate GCP Cloud Certification