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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
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