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NVIDIA

Designs the chips and software that power AI

Principal Applied Research Engineer - Content Authenticity

Computer VisionConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 15 years of relevant engineering or research experience in deep learning and computer vision, including a 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 skills 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 operating in an R&D environment where requirements evolve.
  • PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.

Responsibilities

  • Set the technical direction for content authenticity AI at NVIDIA by architecting model and pipeline strategy for detecting synthetic and manipulated media and making build-versus-adapt decisions that shape multi-year investment.
  • Design and build 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.
  • Architect end-to-end forensics pipelines, from data strategy and evaluation methodology through deployment, and establish benchmarks and failure-mode analysis for measuring the team's performance.
  • Own accuracy, latency, and throughput tradeoffs, taking models from research prototype to real-time production performance on NVIDIA hardware.
  • Partner with NVIDIA Research to bring state-of-the-art work into production and with AI4M product teams to shape roadmaps based on technical feasibility and industry direction.
  • Serve as the technical authority on media authenticity across the broader organization by mentoring engineers, reviewing designs, and representing NVIDIA's work externally where appropriate.

Desired 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 shift 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.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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