NVIDIA has been transforming computer graphics and accelerated computing for more than 25 years. In the AI era, it's a unique legacy of innovation that's fueled by great technology and amazing people. NVIDIA Maxine is a developer platform for creating and deploying AI features for real-time video communication and content creation (https://developer.nvidia.com/maxine). Maxine provides state-of-the-art AI models for deploying video/audio enhancement and augmented reality features. Maxine also offers end to end pipelines of multiple low latency AI effects accelerated on NVIDIA GPUs.

We are now looking for outstanding engineers to join the NVIDIA Maxine AI team. You will work alongside brilliant engineers on core technologies to solve ambitious computer vision and deep learning problems, especially building and optimizing real-time AI solutions that could run anywhere on cloud or premise.

• 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

• Strong experience of building and optimizing AI model architectures for fast inference such as 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
• 5+ years of relevant engineering or research background in deep learning and/or computer vision
• Hands-on development skills using deep learning libraries and frameworks such as PyTorch/TensorFlow/ONNX, TensorRT/Triton/WinML and other neural processing SDKs
• Collaboration ability to define project scope and roadmap together with the team while independently drive development effort with strong self-motivation
• MS, or PhD in Computer Science, Computer Engineering, or closely related field or equivalent experience

• Experience with AI inference accelerating hardware and building/optimizing models on them
• Background with performance and latency analysis, profiling and tuning of AI workloads
• Experience with CUDA programming, as well as a real passion for optimizing AI system performance
• Experience of building platforms for computer vision such as real-time tracking of human face, gaze and body, as well as avatar animation and modeling.