Responsibilities:
Design and develop recommendation algorithms tailored to user preferences.
Implement scalable systems to deliver real-time recommendations.
Analyze user behavior data to optimize recommendation accuracy.
Collaborate with data scientists and engineers to integrate models into production.
Stay updated on the latest research and advancements in recommendation systems.
Requirements:
Strong expertise in machine learning, collaborative filtering, and deep learning techniques.
Proficiency in Python and frameworks like TensorFlow, PyTorch, or Scikit-learn.
Experience with big data tools (e.g., Hadoop, Spark) and databases.
Familiarity with A/B testing and performance evaluation metrics for recommendation systems.
Bachelor’s or Master’s in Computer Science, AI, or related field.