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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. Learn how Workato helps businesses of all sizes achieve more at workato.com.
Ultimately, Workato believes in fostering a
flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.But, we also believe in
balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.If this sounds right up your alley, please submit an application. We look forward to getting to know you!
Also, feel free to check out why:
We are looking for an exceptional Senior Software Engineer (Search / Retrieval) to join our growing team. In this role, you will lead the design, development, and optimization of intelligent search systems that leverage machine learning at their core. You’ll be responsible for building end-to-end retrieval pipelines that incorporate advanced techniques in query understanding, ranking, and entity recognition. The ideal candidate combines deep expertise in information retrieval and search relevance with hands-on experience applying machine learning to real-world search problems at scale. You will also be responsible to:
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.
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
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