Momenta

Canada

Position OverviewWere hiring candidates with deep expertise in audio signal processing and neural network-based detection. The selected engineer will be responsible for delivering a production-grade, real-time deepfake detection pipeline as part of a time-sensitive, high-stakes 3-month pilot deployment. Design and Deliver Core Detection PipelineLead the development of a robust, modular deepfake detection pipeline capable of ingesting, processing, and classifying real-time audio streams with high accuracy and low latency. Architect the system to operate under telecom-grade conditions with configurable interfaces and scalable deployment strategies. Model Strategy, Development, and OptimizationOwn the experimentation and refinement of state-of-the-art deep learning models for voice fraud detection. Evaluate multiple model families, benchmark performance across datasets, and strategically select or ensemble models that balance precision, robustness, and compute efficiency for real-world deployment. Latency-Conscious Production ReadinessEnsure the entire detection stack meets strict performance targets, including sub-20ms inference latency. Apply industry best practices in model compression, preprocessing optimization, and system-level integration to support high-throughput inference on both CPU and GPU environments. Evaluation Framework and Continuous TestingDesign and implement a comprehensive evaluation suite to validate model accuracy, false positive rates, and environmental robustness. Conduct rigorous testing across domains, including cross-corpus validation, telephony channel effects, adversarial scenarios, and environmental noise conditions. Deployment Engineering and API IntegrationDeliver a fully containerized, production-ready inference service with REST/gRPC endpoints. Build CI/CD pipelines, integration tests, and monitoring hooks to ensure system integrity, traceability.