Principal Applied Research Engineer, Content Authenticity
Core
Set technical direction and build AI models/pipelines for detecting synthetic and manipulated media (content authenticity) across video, audio, and visual modalities.
Role type
Principal Applied Research Engineer (Content Authenticity)
Builds
Real-time AI solutions for media authenticity, forensics pipelines, and evaluation frameworks.
Domain
Media & Entertainment / Computer Vision / Deep Learning
Deliverable
production ML models
Required skills
Deep learning, Computer vision, Model architecture, Pipeline strategy, Real-time optimization, Technical leadership, Roadmap definition, Cross-functional partnership
Preferred skills
Digital forensics, Media provenance, Synthetic media detection, Standards (C2PA), Evaluation framework design
Technologies
PyTorch, TensorFlow, ONNX, TensorRT, Triton, WinML, Neural processing SDKs
Responsibilities
Architect model and pipeline strategy for synthetic media detection; Design and build efficient AI models for computer vision and video AI; Extend authenticity coverage to audio and other modalities; Architect end-to-end forensics pipelines; Optimize accuracy/latency/throughput tradeoffs for real-time production; Partner with Research and Product teams; Mentor engineers and represent NVIDIA externally.
Seniority
Principal, hands-on IC with strategy & mentorship
