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GrabJobs LogoRecruitment Platform

Scaling Job Search to 10 Million Listings

How Query Quotient built a resilient OpenSearch infrastructure that powers lightning-fast job matching for millions of users across Southeast Asia's most diverse job markets.

10M+
Job Listings
5ms
Avg Query Time
40%
Cost Reduction
GrabJobs Platform Interface

The Challenge

GrabJobs, Southeast Asia's fastest-growing job portal, was facing critical scalability challenges as they expanded across multiple countries. Their existing search infrastructure couldn't keep pace with their explosive growth:

Multi-Language Complexity

Supporting 12+ languages including Thai, Vietnamese, Bahasa, and Chinese with accurate search results was proving impossible with their current setup.

High Write Throughput

Processing 500,000+ new job listings daily was causing severe indexing delays and search inconsistencies.

Complex Matching Requirements

Matching candidates to jobs required sophisticated algorithms considering skills, location, salary, and cultural fit.

Infrastructure Costs

Unoptimized infrastructure was consuming 70% of their technology budget while still underperforming.

Our Solution

Query Quotient designed and implemented a comprehensive OpenSearch solution tailored for GrabJobs' unique multi-market, multi-language requirements:

Multi-Language Search Architecture

We built a sophisticated multi-language search system that handles Southeast Asia's linguistic diversity:

  • Custom analyzers for 12+ languages with dialect support
  • Cross-lingual search capabilities for multilingual job seekers
  • Automatic language detection and query routing
  • Phonetic matching for name variations across cultures

High-Performance Indexing Pipeline

We engineered a distributed indexing system capable of handling massive write loads:

  • Parallel bulk indexing processing 1M+ documents per hour
  • Smart sharding strategy based on geographic regions
  • Near real-time indexing with 30-second visibility SLA
  • Automated data quality validation and cleansing

Intelligent Job Matching Algorithms

We developed sophisticated matching algorithms that go beyond keyword search:

  • ML-based skill extraction and matching
  • Location-aware search with commute time calculations
  • Salary range normalization across currencies
  • Personalized ranking based on user behavior

Cost-Optimized Infrastructure

We redesigned the infrastructure for maximum efficiency:

  • Auto-scaling clusters based on traffic patterns
  • Tiered storage with lifecycle policies
  • Query result caching reducing compute by 60%
  • Multi-region deployment with intelligent routing

The Results

The OpenSearch transformation delivered game-changing results for GrabJobs:

Scale & Performance

  • 10M+ job listings indexed and searchable
  • 5ms average query response time
  • 1M+ queries per minute at peak
  • 99.95% search availability

Business Impact

  • 250% increase in job applications
  • 40% reduction in infrastructure costs
  • 85% improvement in job match quality
  • Expanded to 3 new markets
"Query Quotient didn't just solve our search problems – they transformed how we think about connecting job seekers with opportunities. The multi-language capabilities and lightning-fast performance have been instrumental in our expansion across Southeast Asia. We've seen a 250% increase in successful job matches since the implementation."
— Michael Tan, CTO, GrabJobs

Technologies & Approach

Technologies Used

  • OpenSearch 2.x with custom plugins
  • Machine Learning for job matching
  • AWS infrastructure with auto-scaling
  • Redis for intelligent caching
  • Apache Airflow for data pipelines

Key Innovations

  • Cross-lingual search algorithms
  • Real-time job recommendation engine
  • Geo-distributed search clusters
  • Automated performance optimization
  • Multi-tenant architecture

Project Timeline

1

Assessment & Planning (2 weeks)

Comprehensive analysis of existing infrastructure and requirements gathering

2

Architecture Design (3 weeks)

Custom multi-language search architecture and infrastructure planning

3

Implementation (8 weeks)

Building and deploying the new OpenSearch infrastructure

4

Migration & Optimization (4 weeks)

Zero-downtime migration and performance tuning

Ready to Scale Your Search Infrastructure?

Let's discuss how Query Quotient can help you build a world-class search experience for your platform.