About the Role
We are looking for an expert in biometric recognition and computer vision to help us build a proprietary contactless fingerprint recognition SDK . The core objective is to turn raw images of a hand/finger captured by a smartphone camera into standards-compliant fingerprint templates that can be submitted to government or enterprise APIs for verification. This is not about integrating an existing SDK — we need someone who can architect and deliver the underlying technology .
Fingerprint Template Generation : Develop algorithms to extract usable fingerprint templates from camera-based fingerphotos.
Image Processing Pipeline : Implement preprocessing (segmentation, enhancement, normalization) to make captures usable across lighting, angles, and devices.
Liveness Detection : Integrate Presentation Attack Detection (PAD) to prevent spoofing, aligned with ISO/IEC 30107-3 .
Standards Compliance : Ensure outputs meet ISO/IEC 19794-2, ANSI/NIST ITL, WSQ formats so they can be recognized by government/enterprise systems.
SDK/API Delivery : Package the solution into a developer-friendly SDK or API with full documentation, sample code, and integration support.
Performance & Benchmarking : Test against NIST/NFIQ 2 quality scores and benchmark accuracy, latency, and robustness in real-world conditions.
Integration Support : Work with mobile developers to integrate into iOS/Android apps and with backend teams for API submission.
Proven experience building fingerprint or palm recognition algorithms (minutiae extraction, ridge analysis, template generation).
Strong background in computer vision and image processing (segmentation, denoising, feature extraction).
Hands-on with OpenCV, TensorFlow, PyTorch, CUDA , and mobile deployment (TensorFlow Lite, Core ML).
Familiar with biometric standards : ISO/IEC 19794-2, ANSI/NIST ITL, WSQ compression, NFIQ 2 image quality.
Knowledge of liveness detection / PAD (ISO/IEC 30107-3).
Track record of building SDKs/APIs with developer documentation and integration support.
Experience working with secure systems (root of trust, data encryption, secure provisioning) is a plus.
Advanced degree (MS/PhD) in Computer Vision, Machine Learning, or related field preferred.
A working SDK/API that can take a smartphone-captured fingerphoto and generate a standards-compliant fingerprint template.
Templates are accepted by a government verification API and pass quality scoring (NFIQ 2).
The pipeline is robust to real-world conditions (different devices, lighting, angles).
Liveness detection is integrated and resilient against common spoofing methods.
Deliverables include SDK/API, documentation, sample integration code, and performance benchmarks.
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