Description

You will design and deploy search ranking and retrieval models.

Responsibilities

• Design, develop, and implement search ranking models using Learn to Rank approaches.
• Apply vector search techniques to improve relevance and personalization in search results.
• Develop scalable data pipelines to support retrieval algorithms and feature engineering.
• Collaborate with engineering, product, and UX teams to improve search experience.
• Analyze large-scale behavioral and clickstream data to inform algorithmic decisions.

Required Skills

• 5+ years of experience in e-commerce or similar domains focused on search and ranking.
• Expertise in Learn to Rank, vector similarity search, and retrieval models.
• Proficiency in Python and libraries like 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 (Spark, Hadoop).

Preferred Skills

• Master's or PhD in Computer Science, Machine Learning, Data Science, or related field.
• Experience working in fast-paced environments with quick turnaround timelines.

Key Skills

Education

Master's degree