Valuebound - MLOps Engineer - Data Modeling

Responsibilities :

• Manage Data : Extract, clean, and structure both structured and unstructured data.
• Coordinate Pipelines : Utilize tools such as Airflow, Step Functions, or Azure Data Factory to orchestrate data workflows.
• Deploy Models : Develop, fine-tune, and deploy models using platforms like SageMaker, Azure ML, or Vertex AI.
• Scale Solutions : Leverage Spark or Databricks to handle large-scale data processing tasks.
• Automate Processes : Implement automation using tools like Docker, Kubernetes, CI / CD pipelines, MLFlow, Seldon, and Kubeflow.
• Collaborate Effectively : Work alongside engineers, architects, and business stakeholders to address and resolve real-world problems efficiently.

Requirements :

(ref : hirist.tech)