Applied AI Engineer (Core)

Optimize deep learning models for deployment using Pytorch, ONNX, TensorRT, and other relevant frameworks. Develop and implement techniques for model quantization and compression to reduce memory footprint and increase inference speed. Develop and implement techniques for model obfuscation and secure deployments. Collaborate with AI researchers and developers to integrate advanced performance optimization techniques into our production systems. Analyze and improve existing model architectures for better efficiency and performance. Interface with production engineering team for assistance with on-prem deployments. Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field. Experience implementing modern deep learning architectures (transformers, CNNs, etc.). Experience compiling model inference code for deployment. Strong software development skills. Strong familiarity with machine (deep) learning frameworks such as PyTorch, ONNX, and TensorRT. 2+ years industry experience preparing ML models for production.

Reality Defender provides accurate, multi-modal AI-generated media detection solutions to enable enterprises and governments to identify and prevent fraud, disinformation, and harmful deepfakes in real time. A Y Combinator graduate, Comcast NBCUniversal LIFT Labs alumni, and backed by DCVC, Reality Defender is the first company to pioneer multi-modal and multi-model detection of AI-generated media. Our web app and platform-agnostic API built by our research-forward team ensures that our customers can swiftly and securely mitigate fraud and cybersecurity risks in real time with a frictionless, robust solution.