Principal Applied Research Engineer, Content Authenticity

NVIDIA develops accelerated computing and AI technologies, including AI for Media platforms for video and audio enhancement and augmented reality workflows. The Principal Applied Research Engineer will set the technical direction for content authenticity AI, develop and productionize computer vision and deep learning models for synthetic and manipulated media detection, and lead end-to-end forensic pipeline development. The role also partners with research and product teams, mentors engineers, and serves as a technical authority on media authenticity.

Responsibilities:

• Set the technical direction for content authenticity AI at NVIDIA — architecting the model and pipeline strategy for detecting synthetic and manipulated media, and making the build-vs-adapt calls that shape multi-year investment
• Design and build highly capable, efficient AI models for computer vision and video AI across synthetic content detection, AI manipulation identification, and semantic plausibility analysis
• Extend authenticity coverage across modalities, including audio authentication analysis and more
• Architect new end-to-end forensics pipelines, from data strategy and evaluation methodology through deployment — establishing the benchmarks and failure-mode analysis the team measures itself against
• Own the accuracy/latency/throughput tradeoff space, taking models from research prototype to real-time production performance on NVIDIA hardware
• Partner deeply with NVIDIA Research to bring state-of-the-art work into production, and with AI4M product teams to shape roadmap based on what's technically achievable and where the field is heading
• Act as the technical authority on media authenticity for the broader org — mentoring engineers, reviewing designs, and representing NVIDIA's work externally where appropriate