2 days ago
Durham, NC, USA +4 moreMid Level / Senior
H1B sponsor
Base Salary
$124k - $242k/yr
Responsibilities
- Develop GPU-accelerated techniques for generative AI, deep learning, and machine learning workloads.
- Optimize generative AI training and inference for developers and customers on NVIDIA platforms.
- Build and optimize algorithms and contribute to training and inference frameworks, low-level software libraries, and open-source projects.
- Analyze and optimize AI algorithms on modern CPU and GPU architectures.
- Collaborate with hardware, system software, library, programming model, engineering, and research teams to shape next-generation products.
- Publish optimization techniques in developer blogs and present findings at industry conferences.
Requirements
- Master’s degree in Computer Science, Computer Engineering, or a related computational field, or equivalent experience.
- At least 1 year of relevant software engineering or performance-tuning work or research experience.
- Fluency in C/C++ and strong understanding of algorithms and software development.
- Background in accelerated computing, parallel programming, performance analysis, and optimization.
- Hands-on experience with low-level performance optimization.
- Foundational understanding of modern CPU and GPU architectures.
- Strong communication, organization, problem-solving, and prioritization skills.
- Preferred: PhD in a relevant field; experience with training and inference stacks, serving frameworks, pre-training and post-training pipelines; and a strong foundation in linear algebra and numerical methods.
Benefits
- Hybrid work arrangement.
- Eligibility for equity and benefits.
Tech Stack
CC++
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.