Fraud/ML Engineer

Cox Exponential • San Francisco, CA

98d

About The Position

Kled is building the largest opt-in human data network in the world. We are a consumer application where people upload their real photos, videos, and documents and get paid continuously. We then filter, standardize, and license that data to frontier AI labs and enterprises that need fresh, rights-aware training data. Since launching our mobile app in 2026, we have reached #1 on the App Store (Finance) with 0 paid marketing, scaled to 200,000+ active data contributors, processed 1.5–3M uploads per day, and raised $5M+ from investors behind top tech companies. Our mission is to let anyone download the app and earn a real living wage from uploading their data. The ML Engineer - Fraud Detection & Data Quality role is responsible for ensuring that only authentic, high-signal, human data gets through our system, which processes millions of files daily. This involves building systems for AI-generated image & video detection, reverse image search & internet plagiarism rejection, duplicate fingerprinting, copyright risk detection, EXIF/metadata tampering detection, fraud network & device clustering, and human-in-the-loop verification pipelines. This is adversarial ML at scale, not academic benchmarks.

Requirements

• 3+ years in computer vision / machine learning (PyTorch or TensorFlow)
• Production ML deployment experience
• Strong SQL / PostgreSQL skills
• Experience with vector search (FAISS, pgvector, Pinecone)
• Image processing (OpenCV, PIL)
• Comfort shipping backend systems (TypeScript/Deno or similar)

Nice To Haves

• Deepfake detection
• Reverse image search systems
• Copyright detection pipelines
• Trust & Safety infrastructure

Responsibilities

• Build AI-generated image & video detection systems
• Build reverse image search & internet plagiarism rejection systems
• Build duplicate fingerprinting (vector + perceptual hashing) systems
• Build copyright risk detection systems
• Build EXIF / metadata tampering detection systems
• Build fraud network & device clustering systems
• Build human-in-the-loop verification pipelines

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed