About the Role
NVIDIA is hiring software engineers for its AI Computing team to build inferencing software used across its product lines. Academic and commercial groups globally are leveraging GPUs for a deep learning-powered AI revolution, leading to breakthroughs in areas such as LLMs, ChatGPT, and GenerativeAI, marking a pivotal "iPhone moment" for AI. This role involves crafting and developing robust inferencing software scalable to multiple platforms, focusing on functionality and performance. The successful candidate will also be responsible for performance analysis, optimization, and tuning, while staying abreast of academic developments in artificial intelligence and updating TensorRT features accordingly. Collaboration with software, research, and product teams across the company is key to guiding the direction of machine learning inferencing. This is an exciting opportunity to contribute to and push the boundaries of state-of-the-art AI and Compute systems, gaining exposure to the entire Deep Learning software stack and helping build the GPU-accelerated DL platform used worldwide.
Responsibilities
- Craft and develop robust inferencing software that can be scaled to multiple platforms for functionality and performance
- Performance analysis, optimization and tuning
- Closely follow academic developments in the field of artificial intelligence and feature update TensorRT
- Provide feedback into the architecture and hardware design and development
- Collaborate across the company to guide the direction of machine learning inferencing, working with software, research and product teams
- Publish key results in scientific conferences
Requirements
- Masters or higher degree in Computer Engineering, Computer Science, Applied Mathematics or related computing focused degree (or equivalent experience)
- 2+ years of relevant software development experience.
- Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.
- Strong curiosity about artificial intelligence, awareness of the latest developments in deep learning like LLMs, generative and recommender models
- Experience working with deep learning frameworks like TensorFlow and PyTorch
- Proactive and able to work without supervision
- Excellent written and oral communication skills in English