$ echo $IMPACT_METRICS
600M+
Profiles
60%
Faster Hiring
$ cat tech-stack.json
$ cat README.md
RecruitBot is an AI-powered recruitment platform that streamlines hiring using ML-powered candidate matching from a database of over 600 million profiles. The platform reduces time-to-fill by up to 60%.
$ git log --oneline responsibilities/
Developed core backend services using Django and Django REST Framework for secure, high-performance APIs
Enhanced scalability by migrating performance-sensitive endpoints to Scala microservices
Built Swagger-documented APIs for web/mobile clients and admin dashboards
Optimized database performance in MySQL and MongoDB with efficient indexing strategies
Collaborated with product & UX on data contracts and feature toggle implementation
Employed comprehensive testing for reliability under evolving product demands
$ grep -r "achievement" ./
Contributed to platform matching 600M+ candidate profiles with ML algorithms
Enhanced scalability during rapid growth with Scala microservices migration
Improved API reliability through documentation and testing practices
Supported 60% faster hiring workflows for recruiting teams
$ cat CHALLENGES.md
Scaling Candidate Search
🔴 Challenge:
Searching 600M+ profiles with complex filtering was slow and resource-intensive.
🟢 Solution:
Migrated search-heavy endpoints to Scala for better performance. Implemented Elasticsearch for full-text search and optimized MySQL with composite indexes.
$ cat details.md
AI-Powered Recruitment
Building for HR Tech with AI meant:
- Large-scale data processing (600M+ profiles)
- ML pipeline integration for candidate matching
- Performance optimization for real-time search
- Privacy considerations for sensitive data
Related
Technologies: Django, Python, Celery, PostgreSQL, MongoDB
Similar Roles: AI Backend Lead at Anaqua | Web Production at Launch Potato