Senior Search Engineer, Acryl Data

• 7+ years of software engineering experience, with at least 4 years focused on search systems
• Deep expertise with Elasticsearch, including:
• Cluster administration and optimization
• Query and indexing performance tuning
• Relevance scoring and ranking
• Text analysis and processing
• Monitoring and observability
• Strong experience with relevance engineering and information retrieval concepts
• Proficiency in performance analysis and optimization techniques
• Experience with large-scale data processing and distributed systems
• Strong coding skills in Java, Python, or similar languages
• Experience with search metrics (NDCG, MRR, etc.) and A/B testing

Desirable

• We're seeking an experienced Search Engineer to optimize and scale our search infrastructure built on Elasticsearch
• In this role, you'll be responsible for delivering lightning-fast, highly relevant search experiences across massive datasets
• You'll work on complex challenges involving search relevance, performance optimization, and scalability while maintaining sub-100ms response times
• This role combines deep technical expertise in search systems with a data-driven approach to relevance tuning
• Architect and optimize Elasticsearch clusters for high-throughput, low-latency operations
• Implement and tune caching strategies to optimize query performance
• Design and implement efficient indexing strategies for large-scale data ingestion
• Monitor and optimize cluster health, performance metrics, and resource utilization
• Implement horizontal scaling solutions while maintaining consistent performance
• Design and implement efficient replication and sharding strategies
• Develop and tune ranking algorithms to improve search relevance
• Implement advanced text analysis pipelines using analyzers, tokenizers, and filters
• Design and implement custom scoring functions and boosting strategies
• Create and maintain relevance testing frameworks
• Conduct A/B tests to measure and improve search quality
• Implement semantic search capabilities using vector search and relevant plugins
• Design and implement efficient search APIs and query DSL patterns
• Build robust monitoring and alerting for search infrastructure
• Develop tools for search quality analysis and debugging
• Implement advanced features like faceted search, autocomplete, and filtering
• Create documentation and best practices for search implementation