Biometric Algorithm & SDK Engineer (Contactless Fingerprint Recognition)

Ontrac Solutions

France

A distancia

EUR 90.000 - 150.000

Jornada completa

14 días+

Una candidatura completa en un minuto

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Descripción de la vacante

Talantir in France is seeking an expert in biometric recognition and computer vision to architect and deliver a standalone fingerprint SDK that converts smartphone fingerphotos into ISO/IEC 19794-2 templates for government and enterprise APIs.

You will build robust processing pipelines, integrate liveness detection, ensure NFIQ 2 quality, and provide documentation, samples, and developer support for iOS/Android.

Formación

  • Proven experience building fingerprint or palm recognition algorithms.
  • Strong background in computer vision and image processing techniques.
  • Hands-on with modern ML frameworks and mobile deployment.
  • Familiar with biometric standards ISO/IEC 19794-2 and NIST/NFIQ 2.
  • Experience delivering SDKs/APIs with developer documentation.

Responsabilidades

  • Fingerprint Template Generation: develop algorithms for templates from fingerphotos.
  • Image Processing Pipeline: segmentation, enhancement, normalization across lighting/angles.
  • Liveness Detection: integrate PAD per ISO/IEC 30107-3.
  • Standards Compliance: ensure outputs meet ISO/IEC 19794-2 and ANSI/NIST ITL.
  • SDK/API Delivery: package solution with docs, samples, and integration support.
  • Performance & Benchmarking: test against NIST/NFIQ 2 quality scores.
  • Integration Support: assist mobile and backend teams for API submission.

Conocimientos

Fingerprint recognition
Image processing
Computer vision
Mobile deployment
Documentation support

Educación

MS/PhD in Computer Vision or ML

Herramientas

OpenCV
TensorFlow
PyTorch
CUDA
TensorFlow Lite / Core ML

Descripción del empleo

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.

Responsibilities
  • 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.
Qualifications
  • 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.
What Success Looks Like
  • 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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