Team Lead

Team Lead – Search & Personalization

Experience: 6–9 years

Location: Bengaluru

Work Mode: Full-time, Work from Office

About the Role

We are looking for someone who has deep, hands-on experience in Search, Relevance and Information Retrieval and has worked on evolving search systems in high-scale consumer internet environments. The ideal candidate would have experience in companies such as Swiggy, Meesho, Flipkart, Amazon, Myntra, Zomato, Zepto or similar environments, where they have worked on search at scale and evolved it from traditional retrieval and ranking towards AI/ML-powered search

and personalization.

What You’ll Do

● Own the Search & Personalization charter end-to-end, including technical roadmap, architecture and execution.

● Build and scale search and information retrieval systems that deliver highly relevantresults.

● Improve search through query understanding, retrieval, ranking, re-ranking and personalization.

● Drive the evolution of search from traditional keyword-based approaches to semantic and AI-powered search.

● Work with ML, NLP, embeddings, vector search and LLM-based approaches to improve relevance and discovery.

● Define and improve search relevance metrics, experimentation frameworks and A/B testing.

● Work closely with Product, Data Science and Engineering teams to solve complex search and discovery problems.

● Lead a team of engineers, provide technical direction and mentor team members.

● Remain hands-on with architecture, technical design and critical engineering problems.

● Build systems that are scalable, reliable and low-latency for a high-volume consumer platform.

What We’re Looking For

● 6–9 years of software engineering experience, with strong and significant experience specifically in Search, Relevance, Information Retrieval or Personalization.

● Experience working at a Team Lead / technical leadership level, owning a significant engineering charter.

● Strong fundamentals in Information Retrieval, including indexing, retrieval, ranking, relevance and query understanding.

● Hands-on experience with search technologies such as Elasticsearch, OpenSearch, Solr, Vespa or similar.

● Experience with ranking, learning-to-rank, re-ranking and recommendation systems.

● Experience with semantic search, embeddings, vector search and hybrid retrieval.

● Experience applying ML/NLP/LLMs to search, discovery or personalization.

● Strong software engineering and distributed systems fundamentals.

● Experience building search or discovery systems in high-scale consumer-facing products.

● Strong product mindset with an understanding of how search quality impacts user engagement, discovery and conversion.

Preferred Background

We particularly value candidates who have worked in consumer internet, e-commerce, marketplace or food-tech environments such as Swiggy, Meesho, Flipkart, Amazon, Myntra, Zomato, Zepto or similar companies. Candidates should ideally have seen search evolve over time and have hands-on experience taking search from traditional retrieval/ranking systems towards AI-driven relevance,

personalization and semantic discovery.