Head of Algorithms

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:

• 7 years of hands-on experience in deep learning and computer vision, with at least 4 years in a leadership role.

• 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