ABOUT MYNTRA:
Myntra is India's leading fashion and lifestyle e-commerce platform, serving millions of customers daily. Our Search & Discovery team powers the first and most critical touchpoint on the app — connecting customers to the right products across a catalogue of 20M+ styles. We operate at the intersection of large-scale ML, real-time systems, and deep domain knowledge of fashion
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THE ROLE:
We're looking for an E5 Architect for Search Relevance — someone who combines deep ML and NLP expertise with the systems thinking to stitch it all together. This is not a pure research role. You will own the end-to-end relevance stack: from query understanding and semantic retrieval through ranking models and experimentation infrastructure. You'll be the technical anchor for the team, setting the direction for how Myntra's search understands, interprets, and serves intent at scal
e.You'll work closely with engineering, product, and data teams to translate ML breakthroughs into production systems that directly impact GMV,
conversion, and customer experience
WHAT YOU'LL DO
Search Intelligence &
NLP Design and own the query understanding pipeline: intent classification, category prediction, attribute extraction, query rewriting, and spell correction.
Build and fine-tune LLMs and task-specific models for fashion-domain query comprehension — handling the full spectrum from head queries to long-tail and zero-result cases.
Own the autocomplete experience end-to-end: suggestion models, personalised typeahead, trending and session-aware completions, and quality evaluation.
Drive hybrid search — defining the architecture for blending dense (bi-encoder, cross-encoder) and lexical signals, and owning the embedding models that power semantic retrieval.
Tackle low-recall and zero-result queries through query expansion, taxonomy mapping, and semantic fallback strategies
Drive rigorous evaluation — offline judgment sets, NDCG