We are now looking for a Software Development Engineer to help TensorRT LLM and TensorRT Edge LLM projects! 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 large language models
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++ 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
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.
Skills Required
- Masters or higher degree in Computer Engineering, Computer Science, Applied Mathematics or related (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
- Experience working with deep learning frameworks like TensorFlow and PyTorch
- Strong curiosity about artificial intelligence and awareness of latest developments in deep learning/LLMs
- Proactive and able to work without supervision
- Excellent written and oral communication skills in English
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
