Description

You will build and optimize search ranking systems using machine learning.

Responsibilities

• Design, implement, and optimize search ranking models using Learning to Rank (LTR) approaches.
• Develop and fine-tune vector search and retrieval algorithms to improve search accuracy.
• Analyze large-scale search logs and user behavior data to find areas for improvement.
• Collaborate with product managers and engineers to deliver data-driven search solutions.
• Experiment with and deploy machine learning models into production search pipelines.

Required Skills

• 5+ years of experience as a Data Scientist or ML Engineer in e-commerce or search.
• Proven expertise in Learning to Rank, vector similarity models, and retrieval systems (BM25, ANN, Faiss, Elasticsearch, Pinecone).
• Strong proficiency in Python, including libraries like Scikit-learn, TensorFlow, or PyTorch.
• Experience processing large datasets using distributed computing frameworks like Spark or Hadoop.
• Solid understanding of NLP and information retrieval concepts.

Key Skills

Education

Any Gradute