HybridRank — Redrob Intelligent Candidate Ranker

Paste one or more candidate profiles as JSONL (one JSON object per line). The ranker will score and rank them for the Senior AI Engineer JD.

Candidate JSONL input (one candidate per line)

{"candidate_id": "CAND_0000001", "profile": {"anonymized_name": "Test User", "headline": "ML Engineer", "summary": "ML engineer with production experience in embeddings and vector search.", "location": "Pune", "country": "India", "years_of_experience": 6.0, "current_title": "ML Engineer", "current_company": "Acme Corp", "current_company_size": "201-500", "current_industry": "Technology"}, "career_history": [{"company": "Acme Corp", "title": "ML Engineer", "start_date": "2020-01-01", "end_date": null, "duration_months": 53, "is_current": true, "industry": "Technology", "company_size": "201-500", "description": "Built embedding-based retrieval and ranking systems using FAISS and sentence-transformers. Deployed vector search at scale with NDCG evaluation."}], "education": [{"institution": "IIT Bombay", "degree": "B.Tech", "field_of_study": "Computer Science", "start_year": 2014, "end_year": 2018, "grade": "8.5 CGPA", "tier": "tier_1"}], "skills": [{"name": "Python", "proficiency": "expert", "endorsements": 20, "duration_months": 60}, {"name": "Machine Learning", "proficiency": "advanced", "endorsements": 15, "duration_months": 48}, {"name": "FAISS", "proficiency": "advanced", "endorsements": 8, "duration_months": 36}, {"name": "NLP", "proficiency": "advanced", "endorsements": 10, "duration_months": 40}], "certifications": [], "languages": [{"language": "English", "proficiency": "professional"}], "redrob_signals": {"profile_completeness_score": 88, "signup_date": "2023-06-01", "last_active_date": "2025-05-20", "open_to_work_flag": true, "profile_views_received_30d": 45, "applications_submitted_30d": 3, "recruiter_response_rate": 0.82, "avg_response_time_hours": 4.0, "skill_assessment_scores": {"Python": 88, "Machine Learning": 76}, "connection_count": 320, "endorsements_received": 53, "notice_period_days": 30, "expected_salary_range_inr_lpa": {"min": 25, "max": 40}, "preferred_work_mode": "hybrid", "willing_to_relocate": true, "github_activity_score": 72.0, "search_appearance_30d": 18, "saved_by_recruiters_30d": 5, "interview_completion_rate": 0.9, "offer_acceptance_rate": -1, "verified_email": true, "verified_phone": true, "linkedin_connected": true}}

Ranked CSV output

How to use: Paste any number of candidate JSON objects (one per line) into the left box and click Run Ranker. The sample pre-loaded is a single strong AI/ML candidate profile.