Lead Applied Scientist, Search and Information Retrieval

About the role

This position leads the creation and production rollout of large scale search and retrieval systems used by legal, tax and accounting products. The work supports several product teams and is judged by measurable results in production.

What you will do

• Design and launch search architectures that handle very large legal, tax and enterprise content sets
• Create and tune ingestion pipelines that parse, enrich and ready documents for retrieval
• Build ranking and re-ranking systems that combine classical IR methods with modern LLM techniques
• Raise retrieval quality using semantic and hybrid retrieval, query understanding and relevance tuning
• Define evaluation frameworks covering retrieval performance, relevance, ranking quality and user outcomes
• Guide technical choices on indexing, retrieval architecture, ranking models and search infrastructure

What they look for

• At least eight years of industry work on production search, retrieval, ranking or recommendation systems
• Publications at venues such as SIGIR, ACL, EMNLP, NeurIPS, ICLR, KDD or WWW
• Strong production Python plus PyTorch, Hugging Face Transformers and distributed model development
• Knowledge of search engine architecture, indexing systems and ingestion pipelines
• Hands-on work building ranking and re-ranking systems, not only using search technologies

Nice to have

• Building retrieval systems over large enterprise knowledge repositories
• Experience with Elasticsearch or OpenSearch