NVIDIA is hiring software engineers for its AI Computing team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning-powered AI, enabling breakthroughs in areas like LLM, ChatGPT and GenerativeAI that has put DL at the “iPhone moment” for AI. Join the team which is building the inferencing software which will be used across our product lines! The ability to work on a fast-paced delivery-focused team is required and excellent interpersonal skills are a must.
What you'll be doing:
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-LLM
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
What we need to see:
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++ or Python 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 models
Experience working with deep learning frameworks PyTorch, TensorRT-LLM, SGLang, vLLM
Proactive and able to work without supervision
Excellent written and oral communication skills in English
NVIDIA is widely considered to be one of technology’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. Does the idea of contributing to and pushing the boundaries of state-of-the-art AI and Compute systems excite you? Interested in getting exposure to the entire DL SW stack? Come join us and help build the GPU-accelerated DL platform used worldwide.