3 days ago
Base Salary
$184k - $357k/yr
Responsibilities
- Develop GPU-accelerated techniques for generative AI, deep learning, and machine learning workloads.
- Optimize generative AI training and inference on NVIDIA platforms in collaboration with key developers.
- 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 engineering and research teams on next-generation hardware, system software, libraries, and programming models.
- Publish optimization techniques in developer blogs and present at industry conferences.
Requirements
- Master’s degree in Computer Science, Computer Engineering, or a related computational field, or equivalent experience.
- 8+ years of relevant software engineering or research experience with performance tuning.
- Programming fluency in C and C++ with strong knowledge 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: expertise optimizing LLM, diffusion model, and multimodal architecture training and inference.
- Preferred: experience with training and inference stacks, serving frameworks, and pre-training and post-training pipelines.
- Preferred: strong foundation in linear algebra and numerical methods.
Benefits
- Hybrid work arrangement.
- Eligible 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.