Description

You will design and deploy search ranking and retrieval models to improve relevance and personalization.

This role is remote.

Responsibilities

• Design and implement search ranking models using Learn to Rank approaches.
• Apply vector search techniques to enhance search result quality.
• Build scalable data pipelines for retrieval algorithms and feature engineering.
• Collaborate with engineering, product, and UX teams to refine the search experience.
• Analyze large-scale behavioral and clickstream data to guide algorithmic decisions.

Required Skills

• 5+ years of experience in search and ranking within e-commerce or similar domains.
• Expertise in Learn to Rank, vector similarity search, and retrieval models.
• Proficiency in Python with scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Experience with search engines (Elasticsearch, Solr, Vespa) and ANN frameworks (Faiss, Annoy, Milvus).
• Solid understanding of information retrieval concepts, relevance metrics, and evaluation methods.
• Experience prototyping and iterating on models with measurable business impact.
• Familiarity with large-scale data processing using Spark or Hadoop.

Preferred Skills

• Master's or PhD in Computer Science, Machine Learning, Data Science, or related field.

Key Skills

Education

Master's degree