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Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility. Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in today’s fast-changing world.
Job Responsibility:
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 our search cluster that can scale to millions of documents across customers and data sources
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
Drive improvements in query construction, indexing and search performance
Be up-to-date with the latest improvements in search and indexing technologies
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