Description

You will design and optimize recommendation systems while building scalable machine learning pipelines for real-time and batch processing.

This role is hybrid.

Responsibilities

• Design, develop, and optimize recommendation systems using collaborative filtering, content-based, and hybrid approaches.
• Build and maintain scalable ML pipelines for both real-time and batch processing.
• Partner with Data Science, Engineering, and Product teams for end-to-end deployment.
• Evaluate model performance using precision, recall, and user engagement metrics.
• Implement advanced methodologies including reinforcement learning and graph neural networks.

Required Skills

• 5+ years of hands-on experience in machine learning with a strong focus on recommendation systems.
• PhD in Computer Science, Machine Learning, Data Science, or a related field.
• Strong programming expertise in Python.
• Proficiency with machine learning frameworks such as TensorFlow and PyTorch.
• Deep understanding of algorithms including matrix factorization, neural networks, clustering, and ranking systems.
• Experience working with cloud platforms and big data tools such as AWS and Databricks.

Key Skills

Education

Any Gradute