1 day ago
Base Salary
$184k - $357k/yr
Responsibilities
- Design, build, and optimize agentic AI systems for the CUDA ecosystem.
- Develop agent abstractions, GPU-centric runtimes, and compiler- or runtime-driven solutions for agent planning, tool use, code generation, and related AI workloads.
- Co-design systems with software, hardware, and algorithm teams and help incorporate new capabilities into NVIDIA products.
- Develop reproducible, high-fidelity evaluation frameworks covering performance, quality, and developer productivity.
- Collaborate across hardware, compilers and toolchains, kernels and libraries, frameworks, distributed training, inference and serving, and model and agent teams.
Requirements
- Bachelor’s degree in Computer Science, Electrical Engineering, or a related field, or equivalent experience; an MS or PhD is preferred.
- 8+ years of industry or academic experience developing AI systems.
- Experience with foundational models, agents, or orchestration frameworks and hands-on experience with deep learning frameworks and modern inference stacks.
- Strong C/C++ and Python programming skills with solid software engineering fundamentals.
- Experience with GPU programming and performance optimization using CUDA or an equivalent technology.
- Preferred experience includes building or evaluating deep learning models, coding agents, developer tooling, high-performance model deployment, GPU optimization, reinforcement learning, multi-agent systems, and open-source or research leadership.
Benefits
- Competitive salary, equity, and benefits package.
- Base salary varies by location, experience, and comparable employee pay; the stated ranges are for Level 4 and Level 5.
- Applications are accepted at least until October 20, 2026.
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.