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 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 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