Description

Automate machine learning workflows and manage the end-to-end lifecycle of deployed models.

Responsibilities

• Automate machine learning workflows from data preparation and model training to deployment and monitoring.
• Implement CI/CD pipelines specifically for machine learning systems.
• Monitor and manage the performance of deployed models to ensure accuracy and efficiency.
• Develop best practices for model versioning, testing, and deployment to ensure reproducibility.
• Collaborate with data scientists and engineers to integrate new MLOps technologies into existing processes.

Required Skills

• 5+ years of professional experience.
• Proficiency in Python and familiarity with R, Java, or Scala.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras.
• Strong understanding of data processing using Pandas, NumPy, or Apache Spark.
• Hands-on experience with Docker and Kubernetes for containerized applications.
• Proficiency with CI/CD tools including Jenkins, GitLab CI/CD, Travis CI, or CircleCI.
• Experience with AWS services, including compute, storage, and AWS SageMaker.
• Knowledge of configuration management and orchestration using Ansible, Chef, or Puppet.
• Understanding of MLOps principles for model deployment and management.

Key Skills

Education

Any Graduate