Senior Math Libraries Engineer - LLM Integration and Developer Experience

at Nvidia

📍 Santa Clara, United States

USD 152,000-287,500 per year

SENIOR

✅ Hybrid

Tech Stack
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AI @ 6 API @ 4 Agentic AI CUDA @ 3 Communication @ 4 Computer Vision GPU LLM Mathematics @ 4 Reinforcement Learning @ 4

Details

We are looking for a passionate and energized engineer to accelerate the integration of APIs across the CUDA-X math library software stack into modern LLM and agentic AI workflows. Leading organizations globally are using GPU-powered data centers for AI, data analytics, and scientific simulations, driving advancements in fields like LLMs, computer vision, CAE, EDA, and autonomous vehicles. Our team develops the GPU-accelerated libraries and SDKs essential for these technologies.

In this role, you will be responsible for ensuring both human engineers using LLMs and AI agents build high-performance applications with ease through effective utilization of CUDA-X libraries. The role requires a blend of technical, developer experience, and communication skills.

Responsibilities

Drive the architecture and implementation of math library APIs and documentation structures designed to be LLM-first: introspectable, explainable, and easily synthesized by AI agents.
Work with internal and external stakeholders to deliver timely LLM-enhanced library releases.
Build metrics, tools, and processes to measure the impact and quality of LLM and agentic code generation.
Prototype tooling and solutions to transform math library APIs into LLM-friendly representations across popular code-generation tools.

Requirements

A PhD or MSc degree in Computational Science, Computer Science, Applied Mathematics, or a related science or engineering field is preferred, or equivalent experience.
3+ years of experience.
Robust knowledge of LLMs, fine-tuning, reinforcement learning, RAGs, MCP, and agent tooling.
Proven experience designing clear, composable APIs and writing high-quality, well-documented code for complex technical domains.
Ability to prioritize multiple projects and work independently with minimal direction.
Excellent collaboration, communication, and documentation habits.

Preferred Qualifications

Prior work in AI-assisted software engineering, code generation, or programming language design.
Familiarity with CUDA-X math library APIs, including cuBLAS, cuFFT, cuSOLVER, and cuSPARSE.

Benefits

Equity and benefits are provided.
NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.
Applications will be accepted at least until September 19, 2026.
NVIDIA uses AI tools in its recruiting processes.