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AI Index Optimization Engineer

Kyle Park

Full-time · Job · Los_Angeles

About the role

Vector search is easy at 1 million documents. At 500 million, everything breaks — index sizes exceed memory, query latency spikes, and the cost of re-indexing after model updates becomes prohibitive. Our search infrastructure serves 500M+ vectors across 30 client deployments, and keeping it fast and affordable is a full-time engineering challenge. You'll optimize the vector index infrastructure: sharding strategies that balance query load, quantization techniques that reduce memory without killing recall, incremental indexing that avoids full rebuilds, and the caching layer that handles hot query patterns without stale results. This is systems engineering with a search-specific flavor. You'll need to understand approximate nearest neighbor algorithms, memory hierarchies, and distributed systems — and how they interact at scale. If you've run vector search in production and know why the benchmark numbers never match reality, we need your experience.

Responsibilities

  • Optimize vector index infrastructure serving 500M+ vectors across 30 deployments
  • Design sharding strategies balancing query load across distributed clusters
  • Implement quantization techniques reducing memory while preserving recall
  • Build incremental indexing avoiding expensive full rebuild operations
  • Monitor and maintain query latency SLAs across all client deployments

Requirements

  • 5+ years in search infrastructure or distributed systems engineering
  • Deep understanding of ANN algorithms and vector index implementations
  • Kubernetes and Docker expertise for distributed system management
  • Experience with memory optimization and index compression techniques
  • Strong Python skills for tooling and performance monitoring

Benefits

  • Fully remote — US West Coast hours
  • Senior compensation with equity
  • $3,000 annual learning budget
  • Working at the cutting edge of vector search at scale

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Categories

MLOps & AI Infrastructure

Skills

python docker kubernetes aws fastapi

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

MLOps & AI Infrastructure

Skills

python docker kubernetes aws fastapi sql

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