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Kled AI

Specializes data marketplace for AI training

Fraud/ML Engineer

Computer VisionConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • At least 3 years of experience in computer vision or machine learning using PyTorch or TensorFlow.
  • Production machine learning deployment experience.
  • Strong SQL and PostgreSQL skills.
  • Experience with vector search using FAISS, pgvector, or Pinecone.
  • Image processing experience with OpenCV or PIL.
  • Ability to ship backend systems using TypeScript, Deno, or similar technologies.

Responsibilities

  • Build AI-generated image and video detection systems.
  • Build reverse image search and internet plagiarism rejection systems.
  • Build duplicate fingerprinting using vector and perceptual hashing.
  • Build copyright risk detection systems.
  • Build EXIF and metadata tampering detection systems.
  • Build fraud network and device clustering systems.
  • Build human-in-the-loop verification pipelines.
  • Own core systems that power the human data network.
  • Design infrastructure that influences what data trains next-generation AI models.

Desired Qualifications

  • Experience with deepfake detection.
  • Experience with reverse image search systems.
  • Experience with copyright detection pipelines.
  • Experience with Trust and Safety infrastructure.

About the Company

Kled AI

Specializes data marketplace for AI training

Kled AI operates as a specialized data marketplace that connects content owners with AI developers. It sources licensed video libraries from film studios and production houses, then processes and labels the footage to create structured, high-quality data for training generative AI models. This data is sold or licensed to AI companies (for example OpenAI and Midjourney) to improve models, including text-to-video systems. Unlike general data brokers, Kled AI focuses on ethically sourced, licensed media and on turning raw video into labeled datasets that meet the needs of model training. Led by David Luan and a co-founder with deep experience in large language models, the company leverages its expertise to streamline data acquisition for AI labs and to create a new revenue stream for content creators. Its goal is to provide reliable data-as-a-service infrastructure that scales the supply of high-quality training data for the generative AI ecosystem.

Company size
11-50
Company stage
Early VC
Total funding
$8.5M
Headquarters
San Francisco, CA
Founded
2025

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