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Perplexity · London

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

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Stack mentioned

etlrustc++pythonapache-kafkahadooplinuxkubernetesawsdata-structures

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. You will help drive key decisions around the architecture, design, and implementation of foundational components in our technical stack.

Responsibilities

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Design and build core search engine components, especially indexing pipelines, data storage formats that operate at the scale of billions of pages

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Develop streaming and batch data processing with YT systems for search index construction in a high-load environment

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Push the limits of hardware performance through low-level optimizations and systems-level tuning

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Tackle challenges in multithreading, concurrency, and system-level optimization

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Design and build core search engine components, including indexing pipelines, retrieval algorithms, and ranking systems that operate at the scale of billions of pages

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Develop streaming and batch data processing systems for search index construction in a high-load environment

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Push the limits of hardware performance through low-level optimizations and systems-level tuning

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Tackle challenges in multithreading, concurrency, and system-level optimization

Qualifications

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3+ years of hands-on experience in systems programming (Rust, C++, C, or similar)

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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

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Knowledge of Python or other scripting languages

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Knowledge of Data processing systems (YT/Kafka/Hadoop)

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Passion for writing clean, efficient, and scalable systems-level code

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Strong knowledge of algorithms and data structures, and the ability to apply them effectively

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Deep understanding of multithreading, including various approaches, challenges, and trade-offs

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Experience building high-load, distributed, and hardware-adjacent services

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Solid understanding of Linux internals (syscalls, networking stack, memory model, kernel tuning)

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Familiarity with low-level optimization techniques (memory management, cache efficiency, SIMD, profiling)

Preferred Qualifications

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Experience developing core components of search engines, databases, or information retrieval systems

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Understanding of search fundamentals: indexing, query parsing, ranking, and relevance

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Experience with trading systems or other latency-sensitive real-time systems

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Familiarity with cloud services, Kubernetes, and AWS infrastructure

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