Head of Algorithms

Description Founded in 2002, AU10TIX is the global leader in AI driven identity verification and management, protecting the world’s largest brands against advanced fraud. The company’s future-proof product portfolio helps businesses provide frictionless customer onboarding and verification in 4-8 seconds while staying ahead of emerging threats and evolving regulatory requirements. We are Looking for Head of Algorithms for: driving continuous improvement in detection rates across all algorithm domains (document fraud, deepfakes, biometrics) while ensuring production-grade performance, scalability, and reliability of deployed models Providing technical direction, mentorship, and career development to the Algo group Set the overall technical strategy and roadmap for all computer vision algorithm development Drive data labeling strategy and ownership across the organization, coordinate with QC, Product and various teams to define intake processes and SLAs Prepare and deliver technical presentations for diverse audiences: client-facing ML capability pitches, VP-level strategy decks, and internal architecture reviews Ensure PII compliance in algorithm pipelines and participate in cross-departmental compliance mapping initiatives Model Development & Research Own and guide the design, training, and optimization of deep learning models for identity document classification, tampering detection, deepfake detection, and biometric analysis Lead model architecture decisions and drive migration to modern architectures ML Lifecycle & Infrastructure Own the end-to-end ML pipeline: data gathering, labeling strategy, training, evaluation, versioning, and deployment Drive cloud migration of training pipelines to Cloud ML (compute clusters, experiment tracking, model registry, CI/CD integration) Oversee inference optimization: ONNX export, TensorRT FP16 acceleration, GPU benchmarking, and microservices packaging Define and maintain evaluation frameworks including demographic fairness testing, ROC/AUC analysis, FAR/FRR metrics, and detection rate tracking at fixed false-alarm thresholds Requirements 10 years of hands-on experience in deep learning and computer vision, with at least 5 years in a senior leadership role managing team leads. Proven experience leading and scaling technical teams in a director-level or equivalent capacity Strong expertise in CNN architectures and computer vision pipelines Production experience with the full ML lifecycle: data collection, labeling, training, evaluation, optimization, and deployment Solid understanding of GPU inference optimization and benchmarking Strong communication skills, ability to present complex ML topics to both technical and non-technical audiences Nice to Have Domain experience in identity verification, document analysis, or fraud detection Experience with deepfake detection (document-level and biometric) Experience with cloud ML platforms (Azure ML preferred: compute clusters, experiment tracking, model registry) Familiarity with unsupervised/semi-supervised methods Knowledge of microservices architecture patterns and containerized deployment (Docker, Kubernetes) Experience with object detection frameworks and segmentation models Background in LLM integration for document extraction tasks