обновлено 12 дней назад
Applied Search & Retrieval Expert
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Applied Search & Retrieval Expert (Search/Retrieval): Building scalable, high-quality, and cost-efficient search and retrieval capabilities across diverse, heterogeneous data contexts with an accent on architecture ownership, relevance evaluation, and production search quality. Focus on designing golden datasets and automated metrics, diagnosing indexing and ranking failures, and balancing quality, latency, cost, and complexity.
Location: Belgrade, Serbia — hybrid
Company
develops a brand management platform used by companies worldwide to create consistent brand experiences.
What you will do
- Own and evolve the search and retrieval architecture across existing and expanding search initiatives.
- Design and operate retrieval evaluation systems covering golden datasets, automated metrics, human evaluation, regression testing, and failure analysis.
- Define technical decision principles for what to build, buy, tune, simplify, or skip.
- Improve search quality across messy, heterogeneous, and evolving data contexts.
- Diagnose issues across data quality, indexing, embeddings, query formulation, ranking, permissions, product UX, and evaluation design.
- Guide trade-offs between quality, latency, cost, and complexity while sharing expertise with the wider engineering team.
Requirements
- Production experience building, owning, or significantly shaping search and retrieval systems in larger product environments.
- Practical experience with keyword, vector, and hybrid search, including ranking, reranking, query understanding, chunking, metadata strategies, and relevance tuning.
- Strong knowledge of traditional search technologies, including text analysis, tokenization, BM25, lexical ranking, index architecture, structured retrieval, and permission-aware search.
- Experience designing and operating retrieval evaluation systems with golden datasets, human evaluation, automated metrics, regression testing, and failure analysis.
- Ability to diagnose retrieval issues and communicate trade-offs between quality, latency, cost, and complexity.
- Strong engineering judgment and experience working with messy, heterogeneous, and evolving real-world data.
Nice to have
- Experience with OpenSearch or comparable enterprise search technologies.
- Experience supporting reliable, secure, and well-scoped MCP server capabilities.
- Experience migrating or evolving production search systems without significant downtime or disruption.
Culture & Benefits
- Flexible working hours and a focus on work-life balance.
- Yearly retreats, workshops, hackathons, and other team activities.
- Knowledge-sharing sessions, webinars, and opportunities for professional growth.
- Collaboration with an international team of experienced engineers.
- Modern, open workplace with a positive and collaborative atmosphere.
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