Position Overview
Weβre 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.
π Design and Deliver Core Detection Pipeline
Lead 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.
π Model Strategy, Development, and Optimization
Own 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.
π Latency-Conscious Production Readiness
Ensure 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.
π Evaluation Framework and Continuous Testing
Design 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.
π Deployment Engineering and API Integration
Deliver 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.
Experience
4 Years
No. of Openings
1
Education
B.Sc, B.Tech, LLM, Ph.D/Doctorate, Any Doctorate Degree
Role
ML Engineer
Industry Type
Engineering / Cement / Metals
Gender
[ Male / Female ]
Type of Job
Full Time
Work Location Type
Work from Home