Computer Vision Engineer for Sports Card Recognition
We are seeking a US-based computer vision and full stack developer to build a platform for sports card recognition. The project includes developing subscription management, dashboards, and user account features. The ideal candidate will have experience creating scalable applications and integrating computer vision capabilities into a user-friendly platform.
Hiring: Computer Vision + Full Stack Developer for Sports Card Live Auction Overlay App (SaaS)
Overview
I’ve built an MVP of a real-time sports trading card scanning and comping overlay tool using Loveable.dev. The product helps buyers gain an edge during live auctions by instantly identifying cards and showing real-time market comps.
Now I’m looking for a U.S.-based developer (or strong US-aligned freelancer) to take this from MVP → production SaaS.
This is a subscription-based product, so I need someone who can help build something fast, accurate, scalable, and hard to replicate.
What the product does
Users can:
Capture or upload sports trading card images during live auctions (mobile + desktop)
Instantly identify:
Player
Year / set
Parallel / serial number
Pull live market comps
Display a real-time “buy / avoid / fair price” overlay
The goal is speed + accuracy in live buying situations (seconds matter).
⚙️ What I already have
MVP built in Loveable.dev
Basic overlay + UI flow
Initial comp logic concept
Subscription idea (not yet fully implemented)
️ What I need help building (Phase 1 → Scale)
I’m looking for someone to help rebuild and harden the system into a real SaaS product:
1. Computer Vision / OCR Layer
Card detection from images (mobile + desktop)
OCR extraction (player name, set, serial numbers)
Image recognition / matching to known cards
Confidence scoring (very important — must avoid wrong matches)
2. Comp Engine (Core Value)
Integrate or build system for:
eBay sold listings
130point or similar comp sources
Card Ladder / ALT-style pricing logic
Return:
last sale
average comp
trend direction
liquidity estimate
3. Real-Time Overlay System
Lightweight overlay that works during live auctions
Low latency (fast lookup is critical)
Works on mobile + desktop workflows
4. SaaS Infrastructure
User accounts + authentication
Subscription billing (Stripe)
Usage tracking / rate limiting
Admin dashboard
5. Scaling / Production Hardening
API architecture improvements
Database structure
Performance optimization for real-time use
Error handling for imperfect images
Ideal candidate
You should have experience with:
Computer vision (OpenCV, YOLO, or similar)
OCR pipelines
AI image classification or similarity matching
Full-stack SaaS development
Stripe subscriptions
API design (Node.js / Python / Next.js preferred)
Huge plus if you have:
Sports card / collectibles knowledge
Experience with marketplaces or scraping pricing data
Real-time / low-latency systems
Why this is interesting
This is not a generic app. It’s:
A real-time decision engine for high-value collectibles
Built for a passionate, high-spend niche (sports cards)
Subscription-based with strong monetization potential
Designed for speed advantage in live auctions
Requirements
Must be U.S.-based (preferred for communication/time zone alignment)
Must be able to work independently
Must have strong GitHub/code examples
Bonus if you’ve built AI or vision-based SaaS tools before
Budget
Open to:
Hourly or fixed project
To apply, please include:
Relevant CV / GitHub
Past AI / computer vision projects
Any SaaS or startup experience
Your approach to building a real-time image → comp system
Availability per week
Hiring: Computer Vision + Full Stack Developer for Sports Card Live Auction Overlay App (SaaS)
Overview
I’ve built an MVP of a real-time sports trading card scanning and comping overlay tool using Loveable.dev. The product helps buyers gain an edge during live auctions by instantly identifying cards and showing real-time market comps.
Now I’m looking for a U.S.-based developer (or strong US-aligned freelancer) to take this from MVP → production SaaS.
This is a subscription-based product, so I need someone who can help build something fast, accurate, scalable, and hard to replicate.
What the product does
Users can:
Capture or upload sports trading card images during live auctions (mobile + desktop)
Instantly identify:
Player
Year / set
Parallel / serial number
Pull live market comps
Display a real-time “buy / avoid / fair price” overlay
The goal is speed + accuracy in live buying situations (seconds matter).
⚙️ What I already have
MVP built in Loveable.dev
Basic overlay + UI flow
Initial comp logic concept
Subscription idea (not yet fully implemented)
️ What I need help building (Phase 1 → Scale)
I’m looking for someone to help rebuild and harden the system into a real SaaS product:
1. Computer Vision / OCR Layer
Card detection from images (mobile + desktop)
OCR extraction (player name, set, serial numbers)
Image recognition / matching to known cards
Confidence scoring (very important — must avoid wrong matches)
2. Comp Engine (Core Value)
Integrate or build system for:
eBay sold listings
130point or similar comp sources
Card Ladder / ALT-style pricing logic
Return:
last sale
average comp
trend direction
liquidity estimate
3. Real-Time Overlay System
Lightweight overlay that works during live auctions
Low latency (fast lookup is critical)
Works on mobile + desktop workflows
4. SaaS Infrastructure
User accounts + authentication
Subscription billing (Stripe)
Usage tracking / rate limiting
Admin dashboard
5. Scaling / Production Hardening
API architecture improvements
Database structure
Performance optimization for real-time use
Error handling for imperfect images
Ideal candidate
You should have experience with:
Computer vision (OpenCV, YOLO, or similar)
OCR pipelines
AI image classification or similarity matching
Full-stack SaaS development
Stripe subscriptions
API design (Node.js / Python / Next.js preferred)
Huge plus if you have:
Sports card / collectibles knowledge
Experience with marketplaces or scraping pricing data
Real-time / low-latency systems
Why this is interesting
This is not a generic app. It’s:
A real-time decision engine for high-value collectibles
Built for a passionate, high-spend niche (sports cards)
Subscription-based with strong monetization potential
Designed for speed advantage in live auctions
Requirements
Must be U.S.-based (preferred for communication/time zone alignment)
Must be able to work independently
Must have strong GitHub/code examples
Bonus if you’ve built AI or vision-based SaaS tools before
Budget
Open to:
Hourly or fixed project
To apply, please include:
Relevant CV / GitHub
Past AI / computer vision projects
Any SaaS or startup experience
Your approach to building a real-time image → comp system
Availability per week