2 days ago
Base Salary
$184k - $357k/yr
Responsibilities
- Develop agentic workflows that automate code generation, testing, tuning, and optimization across NVIDIA frameworks, compilers, and developer tooling.
- Partner directly with internal engineering teams to identify high-impact use cases, validate proof points, and evolve requirements.
- Build multi-agent orchestration and LLM-native tooling, including workflows that apply changes, measure results, and iterate.
- Integrate agent systems into Git-native workflows and CI pipelines targeting real GPUs.
- Contribute reusable agentic methodologies and tools that help engineering teams across NVIDIA adopt effective practices.
Requirements
- Master’s degree in Computer Science, Engineering, or equivalent experience.
- At least 6 years of experience.
- Strong Python development skills and working knowledge of GPUs or other highly data-parallel systems.
- Demonstrated experience building or supporting AI systems.
- Experience shipping complex projects with minimal direction and adapting technical direction as evidence changes.
- Experience building tools or systems through direct partnership with internal customer or user teams.
- Experience in multi-agent orchestration or LLM workflow automation, compiler infrastructure, autonomous optimization, hardware-aware deep learning performance, code generation systems, or domain-specific languages.
- Preferred qualifications include ML systems evaluation or testing harnesses, internal engineering tools or frameworks, familiarity with emerging ML hardware and kernel programming techniques, and success in ambiguous, self-directed environments.
Benefits
- Equity and benefits are provided.
- Base salary is determined by location, experience, and comparable employee pay.
- The application is expected to remain open at least until September 17, 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.