Fraud/ML Engineer

ABOUT KLED
Kled is building the largest opt-in human data network in the world.
We are not a labeling firm. We are not a task marketplace.
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 600,000+ active data contributors

• Processed 5M uploads per day

Raised $15M+ from investors behind SpaceX, Airbnb, Coinbase, xAI, OpenAI, Anthropic, Spotify, Lyft, Uber, and more

Our mission is to let anyone download the app and earn a real living wage from uploading their data.

ABOUT THE ROLE
ML Engineer - Fraud Detection & Data Quality
Every day, millions of files hit our system.
Your job is to make sure only authentic, high-signal, human data gets through.
You’ll build:
• AI-generated image & video detection

Reverse image search & internet plagiarism rejection
• Duplicate fingerprinting (vector + perceptual hashing)

• Copyright risk detection
• EXIF / metadata tampering detection

Fraud network & device clustering systems
• Human-in-the-loop verification pipelines

This is adversarial ML at scale, not academic benchmarks.
Example:
A user is tasked with uploading a video of themselves taking out the trash. The user uploads a video of their dog. The upload is rejected automatically.
But more complex. More requirements. At scale.

WE’RE LOOKING FOR

3+ years in computer vision / ML (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)

Bonus:

Deepfake detection

• Reverse image search systems
• Copyright detection pipelines

Trust & Safety infrastructure

CURRENT STACK
Backend

PostgreSQL (Supabase) – 100’s of millions of media files

• S3 storage

Deno / TypeScript edge functions

• Python detection pipelines
Frontend

SwiftUI (migrating to Flutter)

• Internal verification tooling
COMPENSATION

Base salary: $150,000 - $250,000

• $750,000 – $1,500,000 equity
We move fast and work hard.
If you're excited to build large-scale adversarial ML systems that sit at the core of next-gen AI data infrastructure, let’s talk.

GROWTH OPPORTUNITY
You’ll join a team operating at the frontier of applied AI data infrastructure.
In this role, you’ll have the opportunity to:

Own core systems that power one of the largest human data networks in the world
• Design infrastructure that directly influences what data trains next-generation AI models
• Build at real scale - millions of uploads per day, adversarial environments, global contributors
• Ship alongside a team that has built marketplaces, AI systems, and products used by millions

If you’re excited to move fast, build systems that matter, and help define how human data powers frontier AI, let’s talk.
Compensation Range: $150K - $250K
Originally posted on Himalayas