Job Overview
Location
Palo Alto, California; San Francisco, California
Job Type
Full-time
Category
Software Engineering
Date Posted
June 3, 2026
Full Job Description
đź“‹ Description
- • Lead the design, development, and optimization of intelligent search systems leveraging machine learning to power enterprise-grade relevance and retrieval.
- • Build end-to-end retrieval pipelines incorporating advanced query understanding, ranking, and entity recognition techniques to enhance search accuracy and user intent inference.
- • Develop and deploy learning-to-rank models that optimize relevance using behavioral signals, dense embeddings, and structured feedback loops.
- • Architect scalable search infrastructure capable of supporting dynamic document corpora, real-time indexing, and high-throughput query processing.
- • Create and maintain graph-based knowledge systems that enrich LLM capabilities through structured relationship data and contextual disambiguation.
- • Improve query rewriting, intent classification, and semantic search using both statistical and neural methods to increase system precision and recall.
- • Design and own evaluation frameworks for offline and online relevance testing, including A/B experimentation and continuous model tuning.
- • Collaborate with product and applied research teams to translate user needs into data-driven search innovations and feature roadmaps.
- • Produce clean, scalable, and maintainable code while influencing system architecture and technical direction across the relevance and platform stack.
- • Enhance document understanding through robust entity recognition pipelines that support entity-aware retrieval and contextual awareness.
- • Apply traditional information retrieval methods (TF-IDF, BM25) alongside modern neural search techniques (vector embeddings, transformer models) to solve real-world search challenges at scale.
- • Implement and refine relevance evaluation metrics such as NDCG, MRR, and MAP to measure and improve system performance.
- • Work within a high-performance engineering team to deliver mission-critical search capabilities for a cloud-native iPaaS platform trusted by 50% of the Fortune 500.
🎯 Requirements
- • Bachelors/Masters/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 including TF-IDF, BM25, and neural search techniques like vector embeddings and transformer models
- • Experience with text processing, NLP, relevance tuning, and relevance evaluation metrics (NDCG, MRR, MAP)
🏖️ Benefits
- • Flexible, trust-oriented culture that empowers employees to take full ownership of their roles
- • Balance of productivity with self-care supported by a vibrant and dynamic work environment
- • Opportunity to work at a Forbes Cloud 100 company and Deloitte Tech Fast 500 winner
- • Recognized as the #1 best company for remote workers by Quartz
Skills & Technologies
About Workato, Inc.
Workato provides low-code/no-code enterprise automation and integration software that connects applications, data, and business processes across cloud and on-premises systems. Its platform offers pre-built connectors, recipes, and AI-powered workflow orchestration for finance, HR, IT, sales, support, and marketing functions. The company enables organizations to automate tasks without extensive coding, reducing manual effort and accelerating digital transformation initiatives. Workato serves mid-market to large enterprises worldwide through a subscription-based SaaS model, emphasizing security, governance, and scalability for complex integrations.
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