Responsibilities
- Lead the design, development, and optimization of intelligent search systems that leverage machine learning at their core.
- Build end-to-end retrieval pipelines that incorporate advanced techniques in query understanding, ranking, and entity recognition.
- 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.
Requirements
- Bachelors/Masters/PhD degree in Statistics, Mathematics or 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
- Strong analytical and problem-solving skills
- Strong communication abilities to explain technical concepts
- Collaborative mindset for cross-functional team work
- Detail-oriented with strong focus on quality
- Self-motivated and able to work independently
- Passion for solving complex search problems
Nice to Have
- Proficiency in Knowledge Graph construction and optimization
