# ML Engineer

**Company:** [Quantum HR](http://jobs.workable.com/companies/xzmWYcCDdMxZRjk8mo8UZY.md)
**Location:** Cairo, Egypt
**Workplace:** hybrid
**Employment type:** Full-time
**Department:** Local Recruitment

[Apply for this job](http://jobs.workable.com/view/78bf1de5-3841-46dd-bf84-76366468fee0)

## Description

**About Us**

Quantum HR is a premier human resources consulting firm dedicated to connecting exceptional talent with leading organizations worldwide. We specialize in providing bespoke recruitment solutions, leveraging deep industry insights and a global network to help companies build high-performing teams by matching them with professionals who truly fit their needs and culture.  
  
**About the Role**

We are hiring a **Machine Learning Engineer** to design, build, and deploy advanced ML models powering Digified’s digital identity verification and contracting platforms.  
You will work on real-world, high-impact problems in **computer vision, biometrics, OCR, fraud detection, and NLP**, delivering production-grade ML systems integrated into APIs and enterprise workflows.

This is a hands-on engineering role focused on taking models from research to scalable, secure, and compliant production environments.  
  
**Key Responsibilities  
**

-   Develop and optimize ML models for face recognition, liveness detection, OCR, fraud detection, and NLP-based document understanding
-   Build and maintain production-grade ML pipelines and APIs for real-time inference
-   Deploy and scale models using MLOps best practices (CI/CD, versioning, monitoring, retraining)
-   Optimize model performance for latency, accuracy, and reliability in production environments
-   Design and manage high-quality datasets with proper annotation and data governance
-   Monitor model performance (drift, accuracy, false acceptance/rejection rates)
-   Collaborate with backend, mobile, DevOps, and product teams to integrate ML systems
-   Ensure secure, compliant ML practices aligned with regulatory and data privacy standards
-   Conduct research and propose improvements in model architectures and system performance

## Requirements

-   3–7 years of experience in Machine Learning, Deep Learning, or Computer Vision
-   Strong Python programming skills
-   Experience with PyTorch and/or TensorFlow/Keras
-   Strong background in at least one of: Computer Vision, NLP, or Fraud Detection
-   Experience with ML deployment (FastAPI, Flask, Docker, Kubernetes)
-   Understanding of MLOps principles (model versioning, monitoring, retraining pipelines)
-   Solid foundation in mathematics (linear algebra, probability, statistics)
-   Experience working with production ML systems  
    **  
    Nice to Have  
    **
-   Experience with face recognition, OCR, or liveness detection systems
-   Exposure to Vision Transformers, Siamese Networks, CRNNs, or LLM-based systems
-   Experience with distributed training or GPU acceleration
-   Familiarity with MLflow or experiment tracking tools
-   Knowledge of identity standards (FIDO, NIST 800-63-3)
-   Background in fintech, regtech, or anti-fraud systems
-   Experience with trust & safety or government-grade systems

## Benefits

-   Work on cutting-edge ML systems in digital identity and fraud prevention
-   High-impact role with production ownership from research to deployment
-   Exposure to enterprise-grade AI systems used in regulated environments
-   Strong engineering culture with cross-functional collaboration
-   Opportunity to work on advanced CV/NLP/biometric systems at scale
-   Career growth in a fast-scaling AI-driven product company