NVIDIA is looking to solve ambitious computer vision and deep learning problems, specifically building and optimizing real-time AI solutions for video streaming and broadcasting that can run on cloud or premise, to enhance video and voice in live streaming and conference calls.
Requirements
- Strong experience of building and optimizing innovative AI model architectures for video use cases
- Strong experience of developing efficient models with model pruning, distillation, post-quantization and quantization aware training
- Experience with analyzing and fine-tuning deep learning pipeline performance
- Experience with building real-time AI models for laptop and cloud use cases
- Hands-on development skills using deep learning libraries and frameworks such as PyTorch/TensorFlow/ONNX, TensorRT/Triton/WinML and other neural processing SDKs
- Experience with AI inference accelerating hardware and building/optimizing models on them
- Background with performance and latency analysis, profiling and tuning of AI workloads
Responsibilities
- Develop highly efficient and low cost AI models and algorithms for computer vision and video AI
- Optimize the performance, latency and power consumption of AI models on low power processors for deep learning acceleration
- Deploying deep learning models and optimize the inference stack for real-time performance
- Deliver the benefits of NVIDIA’s latest hardware and platform software innovations to the Deep Learning
- Closely collaborate with different deep learning software and hardware teams across NVIDIA to influence roadmaps and deliver solutions
Other
- Collaboration ability to define project scope and roadmap together with the team while independently drive development effort with strong self-motivation
- 8+ years of relevant engineering or research background in deep learning and/or computer vision
- BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or related fields (or equivalent experience)
- Creative and autonomous engineer with a real passion for technology
- Applications for this job will be accepted at least until November 1, 2025.
