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Staff Software Engineer - Search Platform

Uber
Sunnyvale, USA
Full-time
Senior · 8+ years experience
Onsite
Discovered 1 weeks ago
Java

Full Job Posting

Basic Qualifications

  • Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • 8+ years of professional software engineering experience, including significant experience designing and building large-scale distributed systems.
  • Strong expertise in distributed systems architecture, concurrency, data structures, algorithms, and performance optimization.
  • Proficiency in one or more systems or backend programming languages, such as Java, Go, Rust or C++.
  • Proven track record of architecting and delivering complex, production-grade infrastructure systems with high availability and scalability requirements.
  • Demonstrated ability to lead technically ambiguous, cross-team initiatives from architecture and design through execution and production adoption.
  • Strong technical judgment, communication, and collaboration skills, with the ability to influence engineering direction across teams.

Preferred Qualifications

  • Hands-on experience with search technologies such as Elasticsearch/OpenSearch, Solr, Lucene, or large-scale proprietary search systems.
  • Deep expertise in search engines and information retrieval systems, including Apache Lucene, OpenSearch, Elasticsearch, or similar technologies.
  • Strong understanding of indexing architectures, inverted indexes, query execution, relevance ranking, and distributed search systems.
  • Experience with vector search algorithms, such as HNSW, IVF, or other large-scale similarity search techniques.
  • Familiarity with semantic search, hybrid retrieval, embedding-based retrieval, retrieval-augmented generation (RAG), and agentic AI architectures.
  • Experience designing storage and compute architectures for large-scale, data-intensive systems, including compute-storage disaggregation, tiered storage, or distributed indexing.
  • Proven ability to drive substantial improvements in infrastructure efficiency, query latency, indexing throughput, or system reliability.
  • Experience evaluating emerging technologies and translating research or industry advancements into practical, production-grade infrastructure.
  • Track record of technical leadership, mentoring senior engineers, and influencing architectural direction across multiple engineering teams.

Responsibilities

  • For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
  • For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
  • For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
  • Build next-generation search infrastructure: Design and develop highly scalable, low-latency, and reliable distributed search systems that power Uber's critical business applications.
  • Advance search and retrieval capabilities: Develop and optimize lexical, semantic, vector, and hybrid search capabilities to support increasingly complex retrieval workloads.
  • Enable AI-native and agentic applications: Evolve the search platform to support emerging AI and agentic workloads, including intelligent retrieval, contextual search, and retrieval-augmented generation (RAG).
  • Drive performance and efficiency: Optimize indexing throughput, query latency, resource utilization, and infrastructure costs across large-scale distributed systems.
  • Solve complex engineering challenges: Tackle problems involving distributed indexing, storage architecture, query execution, data freshness, scalability, and system reliability.
  • Shape platform architecture and strategy: Contribute to technical direction and architectural decisions that enable the platform to evolve with Uber's growing business and AI needs.
  • Collaborate across teams/organizations: Partner with engineering and product teams to understand diverse search requirements and deliver reusable, high-impact platform capabilities.

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