AI Software Engineer, Kernel Libraries - New College Grad 2026

Nvidia

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$124,000–$195,500 / yr
Posted
3 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $198k
This role $160k
$110k most similar roles pay here $252k

This role pays less than 75% of similar roles. Most pay $159,937–$235,750 — the shaded band above. At the midpoint, this role pays about $160k versus about $198k 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 997 open roles on FindRole.

Listed pay typically runs $168,000–$270,250 across 984 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · AI Software Engineer, Kernel Libraries - New College Grad 2026

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Join our team of AI systems engineers at NVIDIA to develop cutting-edge technologies for accelerating AI inference. You will design and build libraries, code generators, and GPU kernel technologies tailored for NVIDIA’s hardware architecture, focusing on efficient attention kernels, LLM inference runtimes components, and just-in-time domain-specific compilers. Collaborate closely with cross-functional teams across deep learning frameworks, libraries, and GPU architectures to innovate and optimize high-impact AI workloads. Ideal candidates have a master's degree in Computer Science or Electrical Engineering, 2+ years of experience in ML/DL systems development, and expertise in Python, C/C++, and GPU kernel development using CUDA C/C++. Strong background in domain-specific compiler solutions for LLM inference engines like vLLM and SGLang is essential.

Skills

Python C++ CUDA cuTelemetry Triton PyTorch JAX TensorFlow ONNX vLLM SGLang MLIR FlashInfer Apache TVM NVIDIA GPU Architecture Deep Learning Frameworks Domain Specific Compilers

What you'll do

  • Design and implement new abstractions for LLM serving engines.
  • Develop efficient attention kernel implementations for AI workloads.
  • Build just-in-time domain-specific compilers and runtimes for AI inference.
  • Optimize GPU kernels to accelerate large language models and agents.
  • Contribute to open-source communities like FlashInfer, vLLM, and SGLang.

What we're looking for

  • Masters degree in Computer Science, Electrical Engineering, or related field; PhD preferred
  • 2+ years of experience in ML/DL systems development
  • Strong expertise in deep learning frameworks and inference engines
  • Proficiency in Python and C/C++ programming
  • Experience with domain-specific compiler solutions for LLM inference
  • Expertise in GPU kernel development and performance optimizations
  • Contributions to open source projects like FlashInfer, vLLM, SGLang

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