Senior Math Libraries Engineer, LLM Integration and Developer Experience

Nvidia

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: —
Salary: $152,000–$241,500 / yr
Posted: 4 days ago
Freshness: Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $225k

This role $197k

$136k most similar roles pay here $304k

This role pays less than 70% of similar roles. Most pay $194,500–$254,750 — the shaded band above. At the midpoint, this role pays about $197k versus about $225k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 908 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 890 roles with salary data.

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At a glance

TL;DR · Senior Math Libraries Engineer, LLM Integration and Developer Experience

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As a Senior Math Libraries Engineer - LLM Integration and Developer Experience, you will join the team developing GPU-accelerated libraries and SDKs for high-performance applications. You will drive the architecture and implementation of math library APIs and documentation structures specifically designed to be introspectable, explainable, and easily synthesized by AI agents. Your daily work involves building metrics, tools, and processes to measure the quality of LLM-generated code while prototyping solutions to transform math libraries into LLM-friendly representations across codegen tools. You will utilize your expertise in LLMs, fine-tuning, RL, RAGs, MCP, and agentic tooling to improve developer experience. The role focuses on the technical challenge of integrating CUDA-X math library software, including cuBLAS, cuFFT, cuSOLVER, and cuSPARSE, into modern AI workflows for fields like computer vision and scientific simulations.

Skills

CUDA-X cuBLAS cuFFT cuSOLVER cuSPARSE LLM RL finetuning Agentic AI Code Generation Parallel Computing

What you'll do

Design and implement math library API architectures that are introspectable and explainable for LLM synthesis.
Develop documentation structures specifically optimized for use by AI agents and human engineers.
Build metrics, tools, and processes to measure the quality of LLM-generated code.
Prototype solutions to transform math library APIs into LLM-friendly representations across common codegen tools.
Deliver timely, LLM-enhanced library releases in coordination with internal and external stakeholders.
Ensure high-performance applications are built easily through effective utilization of CUDA-X libraries.

What we're looking for

PhD or MSc degree in Computational Science, Computer Science, Applied Math, or a related field (preferred).
3+ years of experience.
Robust knowledge of LLMs, fine-tuning, RL, building RAGs, MCP, and agentic 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.
Prior work in AI-assisted software engineering, code generation, or programming language design (preferred).
Familiarity with CUDA-X math library APIs such as cuBLAS, cuFFT, cuSOLVER, and cuSPARSE (preferred).

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