Description

You will support the development of the ML platform to streamline model deployment, monitoring, and scaling ML solutions.

This role is on-site.

Responsibilities

• Collaborate with senior data scientists and cross-functional teams to integrate models into production workflows.
• Build MLOps practices to ensure seamless integration of new data sources and features into models.
• Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
• Document experiments, assumptions, and outcomes while maintaining reproducibility standards.
• Contribute ideas and assist in testing new tools, methodologies, and technologies to improve ML capabilities.

Required Skills

• 2+ years of professional experience in machine learning and MLOps, including ML lifecycle and deployment.
• Proficiency in Python.
• Proficiency in C++.
• Experience with Docker and Kubernetes.
• Experience with MLflow and Apache Airflow.
• Skills in Data Pipelines and Statistics.

Key Skills

Education

Any Graduate