What You’ll Need
6 years of experience building and shipping production ML or applied AI systems
Proven experience owning a retrieval system in production, including vector store selection and operation
Strong Python engineering skills and experience building services/APIs (for example, FastAPI or similar)
Hands-on experience with embeddings, approximate nearest neighbor search concepts, and retrieval or ranking systems
Experience designing indexing and refresh strategies, including data quality controls and safe backfills
Strong judgment on tradeoffs across relevance, latency, cost, and operational complexity
Strong communication skills and ability to collaborate across engineering, product, and research teams
It Would Be a Bonus If You Had
Experience with hybrid retrieval (lexical plus vector), learning-to-rank, or domain-specific reranking
Experience with graph-structured context systems or knowledge graph integration
Experience building e...