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AI Engineer

2 months ago

New York, New York, United States Reality Defender Full time
Job Overview

Reality Defender is a pioneering security platform that offers cutting-edge deepfake detection capabilities. As a leading graduate of Y Combinator and Comcast NBCUniversal LIFT Labs, and backed by DCVC, Reality Defender's innovative technology is developed by a seasoned leadership team with over 20 years of experience in applied research at the intersection of machine learning, data science, and cybersecurity.

Our proactive deepfake and AI-generated content detection technology is designed to defend against present and future fabrication techniques, making us the go-to partner for government agencies and enterprise clients seeking to enhance security and detect fraud.

Key Responsibilities
  • Model Optimization: Optimize deep learning models for deployment using Pytorch, ONNX, TensorRT, and other relevant frameworks to ensure seamless integration with our production systems.
  • Model Compression and Obfuscation: Develop and implement techniques for model quantization and compression to reduce memory footprint and increase inference speed, as well as techniques for model obfuscation and secure deployments.
  • Collaboration and Integration: Collaborate with AI researchers and developers to integrate advanced performance optimization techniques into our production systems, ensuring seamless integration and optimal performance.
  • Model Architecture Improvement: Analyze and improve existing model architectures for better efficiency and performance, driving innovation and excellence in our deepfake detection capabilities.
  • Production Engineering Support: Interface with production engineering team for assistance with on-prem deployments, ensuring smooth integration and deployment of our models.
Requirements
  • Education: Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field.
  • Deep Learning Experience: Experience implementing modern deep learning architectures (transformers, CNNs, etc.) and compiling model inference code for deployment.
  • Software Development Skills: Strong software development skills and familiarity with machine (deep) learning frameworks such as PyTorch, ONNX, and TensorRT.
  • Industry Experience: 2+ years industry experience preparing ML models for production, with a strong understanding of the complexities and challenges involved.