Senior Software Engineer - Deep Learning

Position Overview

NVIDIA has been transforming computer graphics and accelerated computing for more than 25 years. Our team builds state-of-the-art AI models for video streaming and broadcasting deployed on the NVIDIA Maxine platform for real-time video communication and content creation. We are now looking for outstanding engineers to join the NVIDIA AI for media team 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.

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

Requirements & Skills

• 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
• 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)

Ways to stand out from the crowd:

• 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