Fraud/ML Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 257d ago
The date the source published, not the day we noticed it (2026-02-17). Last seen at its source 2h ago.
We have tracked this listing since 5 Oct 2026 (28 days). The employer's own board has carried it every time we have read it, most recently 2 hours ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay
$150k–250k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Ashby employer's own board first seen 28d ago · last seen 2h ago
The listing
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.