Staff AI Engineer

• Lead the development of advanced query understanding systems that parse natural language, resolve ambiguity, and infer user intent
• Design and deploy learning-to-rank models that optimize relevance using behavioral signals, embeddings, and structured feedback
• Build and scale robust Entity Recognition pipelines that enhance document understanding, enable contextual disambiguation, and support entity-aware retrieval
• Architect next-gen search infrastructure capable of supporting highly dynamic document corpora and real-time indexing
• Create and maintain graph-based knowledge systems that enhance LLM capabilities through structured relationship data
• Drive improvements in query rewriting, intent classification, and semantic search, using both statistical and neural methods
• Own the design of evaluation frameworks for offline/online relevance testing, A/B experimentation, and continual model tuning
• Collaborate with product and applied research teams to translate user needs into data-informed search innovations
• Produce clean, scalable code and influence system architecture and roadmap across the relevance and platform stack

• Bachelor's/Master's/PhD degree in Statistics, Mathematics, Computer Science, or another quantitative field
• 7+ years of backend engineering experience with 3+ years in search, information retrieval, or related fields
• Strong proficiency in Python
• Hands-on experience with search engines (Opensearch or Elasticsearch)
• Strong understanding of information retrieval concepts spanning traditional methods (TF-IDF, BM25) and modern neural search techniques (vector embeddings, transformer models)
• Experience with text processing, NLP, and relevance tuning
• Experience with relevance evaluation metrics (NDCG, MRR, MAP)
• Experience with large-scale distributed systems
• Proficiency in Knowledge Graph construction and optimization is a plus
• Strong analytical and problem-solving skills
• Strong communication abilities to explain technical concepts
• Collaborative mindset for cross-functional teamwork
• Detail-oriented with strong focus on quality
• Self-motivated and able to work independently
• Passion for solving complex search problems

Proficiency in Knowledge Graph construction and optimization is a plus

• vibrant and dynamic work environment
• multitude of benefits they can enjoy inside and outside of their work lives