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.
Train/finetune deep learning models in PyTorch on new datasets and per client requirements
Model monitoring and quality assurance for deployed models
ML workflow automation and continuous integration/continuous delivery (CI/CD) for client-facing models
Adopt standard model optimization/compression methods for inference speed-up
Implement model obfuscation and vulnerability checks
Collaborate with both AI and Engineering teams for model/infrastructure needs and performance guidance
Masters in Computer Science with specialization in machine learning/deep learning (ML/DL)
2+ years coding experience in Python; Strong programming skills required
2+ years industry experience with model training/finetuning in PyTorch
[Preferred but not required] Experience finetuning large foundation models, e.g. wav2vec, HuBERT for downstream classification
Experience with automated testing and CI/CD concepts in machine learning workflow
Strong foundation in machine learning and data science
Team player with a positive attitude and good communication skills.
NVIDIA
Document Crunch
Clay
NVIDIA
