Principal Applied Research Engineer, Content Authenticity

Details

NVIDIA AI for Media is a developer platform for creating and deploying AI features for media and entertainment workflows. The platform provides state-of-the-art AI models for video and audio enhancement and augmented reality features, enabling studio-quality audio, high-resolution video enhancement, and effects for live and post-production workflows across local and cloud environments.

The AI for Media team is seeking engineers to work on core technologies addressing ambitious computer vision and deep learning problems, including real-time AI solutions that can run on cloud or on-premises environments.

Responsibilities

• Set the technical direction for content authenticity AI at NVIDIA by architecting model and pipeline strategies for detecting synthetic and manipulated media.
• Make build-versus-adapt decisions that shape multi-year investment.
• Design and build efficient AI models for computer vision and video AI, including synthetic content detection, AI manipulation identification, and semantic plausibility analysis.
• Extend authenticity coverage across modalities, including audio authentication analysis.
• Architect end-to-end forensics pipelines, from data strategy and evaluation methodology through deployment.
• Establish benchmarks and failure-mode analysis for team evaluation.
• Manage accuracy, latency, and throughput tradeoffs while taking models from research prototypes to real-time production performance on NVIDIA hardware.
• Partner with NVIDIA Research to bring state-of-the-art work into production.
• Collaborate with AI for Media product teams to shape the roadmap based on technical feasibility and developments in the field.
• Act as the technical authority on media authenticity across the broader organization.
• Mentor engineers, review designs, and represent NVIDIA's work externally where appropriate.

Requirements

• 15 or more years of relevant engineering or research experience in deep learning and computer vision.
• Track record of setting technical direction for a research area across multiple teams or projects.
• Demonstrated ownership of a system or model family from research concept through production deployment at scale.
• Hands-on development experience with deep learning frameworks and deployment stacks such as PyTorch, TensorFlow, ONNX, TensorRT, Triton, WinML, and other neural processing SDKs.
• Ability to scope ambiguous problems into executable roadmaps, define milestones, and lead development independently.
• Experience influencing product and research roadmaps through technical vision rather than positional authority.
• Strong collaboration and communication skills, with comfort working in an R&D environment where requirements evolve.
• PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.

Preferred Qualifications

• Research or engineering background in digital forensics, media provenance, or content authenticity.
• Publications, patents, or recognized contributions in synthetic media detection or related areas.
• Experience developing synthetic video detection models in adversarial settings where generation methods change faster than detection.
• Familiarity with authenticity standards and industry efforts such as C2PA, or participation in standards bodies and benchmark initiatives.
• Experience building evaluation frameworks and datasets for problems where ground truth is expensive or contested.

Compensation and Benefits

• Base salary range: USD 272,000–431,250 per year, determined by location, experience, and the pay of employees in similar positions.
• Eligible for equity and benefits.
• Applications will be accepted at least until September 12, 2026.
• NVIDIA is an equal opportunity employer committed to an inclusive work environment.