Member of Technical Staff (Search Core, Indexing & Data Pipeline Stream)

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About the role

Perplexity is looking for a highly skilled Expert Systems Engineer to join our Search Core team. For the indexing and data processing stream. This role is critical to building next-generation search products and technologies. Responsibilities - Design and build core search engine components, especially indexing pipelines, data storage formats that operate at the scale of billions of pages - Develop streaming and batch data processing with YT systems for search index construction in a high-load environment - Push the limits of hardware performance through low-level optimizations and systems-level tuning - Tackle challenges in multithreading, concurrency, and system-level optimization - Design and build core search engine components, including indexing pipelines, retrieval algorithms, and ranking systems that operate at the scale of billions of pages - Develop streaming and batch data processing systems for search index construction in a high-load environment - Push the limits of hardware performance through low-level optimizations and systems-level tuning - Tackle challenges in multithreading, concurrency, and system-level optimization Qualifications - 3+ years of hands-on experience in systems programming (Rust, C++, C, or similar) - Ownership of full project lifecycle you don't just write a fast inner loop, you care about how the system is built, deployed, operated, and scaled in production - Knowledge of Python or other scripting languages - Knowledge of Data processing systems (YT/Kafka/Hadoop) - Passion for writing clean, efficient, and scalable systems-level code - Strong knowledge of algorithms and data structures, and the ability to apply them effectively - Deep understanding of multithreading, including various approaches, challenges, and trade-offs - Experience building high-load, distributed, and hardware-adjacent services - Solid understanding of Linux internals (syscalls, networking stack, memory model, kernel tuning) - Familiarity with low-level optimization techniques (memory management, cache efficiency, SIMD, profiling) Nice to have - Experience developing core components of search engines, databases, or information retrieval systems - Understanding of search fundamentals: indexing, query parsing, ranking, and relevance - Experience with trading systems or other latency-sensitive real-time systems - Familiarity with cloud services, Kubernetes, and AWS infrastructure

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