Member of Technical Staff (Search Core, Indexing & Data Pipeline Stream)
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What you'll do
- 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
What they're looking for
- 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
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
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
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)
Preferred Qualifications
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
Company
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