H
AI Summary
Design and develop scalable retrieval systems for high-volume search applications. Work on advanced retrieval pipelines involving federated search, blended result orchestration, and ranking coordination. Collaborate with ranking, ML, platform, and product engineering teams to improve recall quality and search experience.
Key Highlights
Design and develop scalable retrieval systems
Work on advanced retrieval pipelines
Collaborate with ranking, ML, and product engineering teams
Key Responsibilities
Design and develop scalable retrieval systems
Build and optimize backend services in Java
Develop and maintain retrieval infrastructure using Vespa and/or Solr
Implement multi-source retrieval pipelines across structured and unstructured datasets
Optimize query execution, indexing strategies, caching, and relevance performance
Collaborate with ranking, ML, platform, and product engineering teams to improve recall quality and search experience
Technical Skills Required
Benefits & Perks
Remote work
Salary range not explicitly stated
Nice to Have
Experience with federated search systems
Knowledge of result blending and ranking orchestration techniques
Experience building secondary result stacks, recommendation shelves, or carousel-based retrieval systems
Job Description
Job Description
Job Description Recall Engineer Retrieval Systems
Remote
Role Overview
We are looking for a Recall Engineer Retrieval Systems to design and build large-scale, high-throughput retrieval infrastructure powering modern search and recommendation experiences. The ideal candidate will have strong backend engineering expertise, deep understanding of distributed search systems, and experience orchestrating retrieval across multiple data sources.
You will work on advanced retrieval pipelines involving federated search, blended result orchestration, ranking coordination, and secondary result stacks/carousels at scale.
Core Responsibilities
- Design and develop scalable retrieval systems for high-volume search applications.
- Build and optimize backend services in Java for low-latency, high-throughput query processing.
- Develop and maintain retrieval infrastructure using Vespa and/or Solr.
- Design APIs and service interfaces for retrieval orchestration and downstream consumers.
- Implement multi-source retrieval pipelines across structured and unstructured datasets.
- Optimize query execution, indexing strategies, caching, and relevance performance.
- Work with Cassandra and distributed storage systems for retrieval metadata and serving layers.
- Build systems for federated search, result blending, and orchestration across heterogeneous sources.
- Develop mechanisms for secondary result stacks, carousels, and contextual retrieval modules.
- Collaborate with ranking, ML, platform, and product engineering teams to improve recall quality and search experience.
- Monitor system reliability, scalability, latency, and throughput in production environments.
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- Strong experience in Java backend engineering.
- Hands-on experience with Vespa and/or Solr search platforms.
- Experience working with Cassandra in distributed production environments.
- Strong understanding of API design and distributed service architecture.
- Experience building high-throughput, low-latency retrieval systems.
- Solid understanding of distributed systems, scalability, concurrency, and performance optimization.
- Experience with microservices architecture and cloud-native deployment models.
- Strong debugging, profiling, and production troubleshooting skills.
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- Experience with federated search systems.
- Knowledge of result blending and ranking orchestration techniques.
- Experience building secondary result stacks, recommendation shelves, or carousel-based retrieval systems.
- Exposure to multi-source retrieval architectures and hybrid search pipelines.
- Understanding of search relevance, retrieval quality metrics, and ranking systems.
- Familiarity with real-time indexing and distributed query execution.
https://www.linkedin.com/company/hyr-global-source-inc
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