Collective is looking for a Senior RAG Engineer (freelance) to build a reliable, sourced, and traceable AI-powered legal knowledge platform for Morocco and Africa. You will own the entire user question → relevant excerpts → reliable and sourced answer pipeline, making the RAG engine measurable, stable, and improvable.

What You'll Do

Design and implement robust retrieval on a legal corpus using dense (embeddings) and hybrid (BM25 + embeddings) search.
Implement metadata filters based on text type, date, jurisdiction, and version.
Set up reranking with cross-encoders or rerankers to improve result precision.
Define a query understanding strategy, including query rewriting, multi-query, expansion with legal synonyms, and long query management.
Build end-to-end evaluation: create a QA dataset and annotation guidelines, track metrics like Recall@k, MRR, and nDCG, run regression tests, and perform error analysis.
Implement grounding and citation mechanisms for source-based answers, precise citations (document/page/section), and controlled 'no-answer' handling.

What We're Looking For

4+ years of experience in Search, Information Retrieval, Ranking, or ML applied to relevance.
Strong proficiency in Python.
A strong culture of metrics and experimentation, with a proven ability to improve via measurement.
Ability to build robust production systems with a focus on quality, performance, and instrumentation.
Professional mastery of French, with the ability to perform fine reading and relevance judgment on legal content.