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. 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
Requirements
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