Senior Flutter Developer Required for Offline AI-Powered Camera & Image Processing Module

We are developing an enterprise-grade SaaS platform called ID Mitra, an ID Card and Attendance Management solution used by schools, colleges, universities, corporate organizations, and government institutions.

As part of our platform, we are building an advanced AI-powered offline photo capture and enhancement system for Android devices. The objective is to enable users to capture professional-quality ID card photographs directly from a mobile device without requiring an internet connection.

This is not a simple camera application. We are looking for an experienced developer who has worked with Computer Vision, AI inference, image processing, and Flutter performance optimization.

Project Objective

Develop a high-performance Android module that automatically captures, validates, enhances, and processes ID card photographs completely offline.

The user should simply point the camera at the student, and the application should automatically produce a professional passport-style photograph within approximately one second.

Core Features
Camera Module
Flutter Camera Integration
Live Camera Preview
Camera Overlay Guide
Auto Focus
Auto Exposure
Flash Control
Auto Capture when conditions are satisfied
Continuous Face Tracking
Face Detection (Google ML Kit)
Single Face Detection
Eye Open Detection
Smile Detection
Face Angle Detection
Face Distance Validation
Face Quality Score
Live Face Tracking
Face Alignment (MediaPipe)
Face Landmark Detection
Face Rotation
Face Alignment
Face Centering
Facial Pose Estimation
Landmark Validation
Image Processing (OpenCV)
Auto Crop
Face Centering
Perspective Correction
Brightness Adjustment
Contrast Adjustment
White Balance
Gamma Correction
CLAHE Enhancement
Sharpening
Noise Reduction
Blur Detection
Image Quality Analysis
Automatic Resize
Portrait Enhancement (ONNX Runtime)
Natural Portrait Enhancement
Face Detail Improvement
Skin Tone Balancing
Lighting Correction
Facial Detail Restoration
Color Enhancement

Note: We do not want beauty filters or unrealistic face modifications.

Background Processing
Background Removal (MODNet)
Pure White Background Generation
Hair Edge Refinement
Background Quality Validation
Passport Photo Validation
Face Position Verification
Head Size Verification
Top Margin Validation
Chin Position Validation
Automatic Passport Framing
Professional ID Photo Output
Compression
Convert to WebP
Target file size between 100 KB and 150 KB
Maintain high visual quality
Offline Functionality

The complete image processing pipeline must work without an internet connection.

Offline features include:

Camera
AI Processing
Image Enhancement
Background Removal
Compression
Local Storage
Queue Management

Only synchronization should require internet access.

Background Synchronization
SQLite / Drift Database
Upload Queue
Automatic Retry
Background Sync
Upload Progress
Error Recovery
Performance Requirements

The application should meet the following targets on modern mid-range Android devices:

Camera Preview: 30–60 FPS
Face Detection: under 50 ms
Face Alignment: under 40 ms
OpenCV Processing: under 150 ms
Portrait Enhancement: under 250 ms
Background Removal: under 350 ms
Total Processing Time: approximately 1 second

The UI must remain responsive throughout processing.

Required Technologies
Flutter (latest stable)
Dart
Google ML Kit
MediaPipe Face Landmarker
OpenCV
ONNX Runtime Mobile
MODNet (ONNX)
SQLite / Drift
flutter_image_compress
Background Services / WorkManager
Git
GitHub
Developer Requirements

We are looking for someone who has experience with:

Flutter application development
Android native integration
Computer Vision
OpenCV
ONNX Runtime
AI model deployment on mobile
MediaPipe
Performance optimization
Offline-first mobile applications
Memory optimization
Battery optimization
Multithreading and isolates

Experience building AI-powered camera or image-processing applications is highly preferred.

Deliverables

The selected developer will be responsible for:

Complete source code
Clean architecture
Modular codebase
Documentation
Unit tests
Performance optimization
Production-ready implementation
GitHub commits throughout development
Preferred Candidate

We prefer developers who have previously worked on:

Passport photo applications
Document scanning applications
Face recognition systems
AI camera applications
OCR applications
Image enhancement applications
Mobile computer vision projects