- Architect a full-stack Search Platform across all layers of indexing and scoring, query understanding, rewriting and federation, and extensible search experiences.
- Continuously improve search quality through evaluation metrics such as precision@K, recall@K, MRR, and relevance testing with real scientific use cases.
- Engineer sophisticated hybrid search pipelines that blend sparse (keyword), structured (metadata), and dense (vector) retrieval, designing custom ranking logic, reciprocal rank fusion, and relevance tuning.
- Lead by example and write code, review designs, and set the standard for engineering quality on the Search Platform team. Mentor engineers and help grow the team's search and distributed systems expertise.
- Contribute to architectural decisions, technical strategy, and platform-wide improvements to accelerate scientific insight generation.
- Own and operate the Search Platform infrastructure, ensuring high availability, scalability, performance, and observability across indexing, embedding generation, and query execution.
- Develop and maintain backend services and APIs in Python and TypeScript that power search capabilities for scientists, data engineers, and AI applications.
- Ensure security, compliance, and tenant isolation as part of operating search services in enterprise bio-pharma environments.
- Collaborate with Applied AI Scientists to integrate embeddings, transformer models, and chemical fingerprints into production search workflows.
- Architect and implement scientific entity resolution and knowledge graph pipelines to transform raw text into interconnected knowledge.
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