"Automated job application pipeline with intelligent form filling"
A browser automation system that streamlines the job search process by aggregating listings from multiple job boards and automating repetitive application tasks.
Built for job seekers who want to scale their applications efficiently while maintaining personalized responses through configurable profile mapping and intelligent form detection.
Scrapes and normalizes job listings from LinkedIn and ZipRecruiter into a unified pipeline for consistent processing.
Maps user profile data to application fields using a configurable YAML-based label mapping system for high accuracy.
Processes multiple applications in single sessions with randomized delays for natural pacing and detection avoidance.
Maintains browser state across runs with fingerprint persistence for seamless authentication and continuity.
JSON output designed for orchestration with external automation platforms for extended workflow capabilities.
Profile mapping is defined in YAML for easy customization:
# profile.yaml - Field mapping configuration personal: first_name: "John" last_name: "Doe" email: "john@example.com" phone: "+1-555-0123" field_mappings: # Maps form labels to profile fields - labels: ["First Name", "Given Name"] value: "personal.first_name" - labels: ["Email", "Email Address"] value: "personal.email" batch_settings: delay_min: 3000 # ms between actions delay_max: 8000 # randomized for natural pacing max_per_session: 25
Designed and built the complete system architecture including browser automation framework, stealth techniques for reliable scraping, multi-step form navigation, and workflow integration layer.
Created modular architecture allowing easy addition of new job platforms and customization of field mapping logic.
Implemented session persistence, error recovery, and batch processing for robust unattended operation.