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Search Retrieval Engineer Jobs (NOW HIRING)

Adobe, Inc.

Information Retrieval Engineer

San Jose, CA · On-site

Implement semantic search infrastructure and hybrid retrieval systems (semantic + keyword) Data ... Collaborate with prompt engineers and model developers to align retrieval outputs with downstream ...

Adobe

Information Retrieval Engineer

San Jose, CA

Implement semantic search infrastructure and hybrid retrieval systems (semantic + keyword) Data ... Collaborate with prompt engineers and model developers to align retrieval outputs with downstream ...

Leidos

Search Engineer

The engineer will ensure day-to-day reliability of indexing and retrieval services by addressing indexing failures, data issues, search syntax and relevance problems, performance degradation ...

You.com

Senior Search Engineer

San Francisco, CA · On-site +1

$123K - $169K/yr

Advance Search Retrieval/Ranking: Research and apply state-of-the-art methods (NLP, ranking, ML) to ... Work closely with data engineers, ML engineers, and product teams to integrate novel features and ...

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Search Retrieval Engineer information

What are the key skills and qualifications needed to thrive as a Search Retrieval Engineer, and why are they important?

To thrive as a Search Retrieval Engineer, you need a strong background in computer science, information retrieval, and algorithms, often supported by a relevant degree or experience. Familiarity with search platforms like Elasticsearch, Solr, and Lucene, as well as programming languages such as Python or Java, is typically required. Strong problem-solving skills, attention to detail, and effective communication set standout professionals apart in this field. These skills ensure the development and optimization of efficient, user-friendly search systems that deliver accurate results at scale.

What are Search Retrieval Engineers?

Search Retrieval Engineers are specialized software engineers who design, develop, and optimize systems that retrieve relevant information from large datasets, such as search engines or document databases. They work on improving the accuracy, speed, and efficiency of search algorithms, often incorporating natural language processing and machine learning techniques. Their responsibilities may also include indexing data, tuning ranking models, and ensuring that users can find relevant results quickly. Search Retrieval Engineers play a crucial role in organizations that handle vast amounts of information, such as tech companies, e-commerce platforms, and research institutions.

What are some common challenges faced by Search Retrieval Engineers when optimizing search relevance?

Search Retrieval Engineers often encounter challenges such as balancing precision and recall, dealing with ambiguous or sparse queries, and ensuring search results remain accurate as content and user behaviors evolve. Another frequent hurdle is integrating new algorithms or data sources without disrupting existing performance. Collaboration with data scientists, product managers, and UX designers is critical to iteratively test and refine ranking models, ensuring the search experience meets user needs while maintaining system efficiency.

What is the difference between Search Retrieval Engineer vs Data Scientist?

AspectSearch Retrieval EngineerData Scientist
Required CredentialsBachelor's or master's in CS, info retrieval, or related fields; experience with search algorithmsBachelor's or master's in CS, statistics, or related fields; proficiency in data analysis
Work EnvironmentTech companies, search engines, e-commerce platformsResearch labs, tech firms, finance, healthcare
Industry UsageSearch engine development, information retrieval systemsData analysis, predictive modeling, business insights

Search Retrieval Engineers focus on developing and optimizing search algorithms and systems, while Data Scientists analyze data to extract insights. Both roles require strong technical skills and often overlap in data handling, but their primary goals differ: search efficiency versus data-driven decision making.

Infographic showing various Search Retrieval Engineer job openings in the United States as of May 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.
Senior Software Engineer (Search / Retrieval)

Senior Software Engineer (Search / Retrieval)

Workato

Palo Alto, CA

$144K - $189K/yr

Other

Posted 2 days ago

Job description

Responsibilities

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.

RequirementsQualifications / Experience / Technical Skills

  • 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

Soft Skills / Personal Characteristics

  • 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

(REQ ID: 2272)

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