Reality Defender is a groundbreaking security platform offering comprehensive deepfake detection. A Y Combinator graduate, Comcast NBCUniversal LIFT Labs alumni, and backed by DCVC, Reality Defender's proactive deepfake and AI-generated content detection technology is developed by a leadership team with over 20 years of experience in applied research at the intersection of machine learning, data science, and cybersecurity.
With models defending against present and future fabrication techniques, Reality Defender is the best way to detect and deter fraudulent text, audio, and visual content, partnering with government agencies and enterprise clients to enhance security and detect fraud.
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
