Machine Learning Engineer, Retrieval

Role overview Own retrieval quality for AI systems by shaping the information models receive before generating answers. The work spans document preparation, search and ranking, evaluation, and production monitoring, with the goal of making retrieval improvements measurable and reliable.

Responsibilities - Build and tune retrieval pipelines for client documents and data that were not originally structured for search. - Develop and run offline evaluations, checking how well they predict production behavior. - Improve ranking with hybrid keyword and vector search, reranking, and simpler methods where they perform better. - Instrument retrieval in production so quality regressions can be detected early. - Share findings with colleagues and occasionally contribute to technical writing.

Requirements - Practical experience with embeddings, vector search, and diagnosing retrieval failures. - Ability to evaluate retrieval quality and connect measurement results to production outcomes. - Experience applying ranking approaches to real-world data and choosing solutions based on evidence.

Benefits and work setup - Permanent, full-time role based in Lahore or remote. - Mid-to-senior level; compensation is discussed in the first conversation.