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# Software Engineer, DL Kernel Libraries - New College Grad 2027

- **Company:** NVIDIA Corporation
- **Location:** Santa Clara, CA, United States
- **Experience:** Starter
- **Salary:** $108,000.0 - $178,250.0
- **Contract:** Permanent contract
- **Skills:** Adobe Flash, Artificial Intelligence, Apache HTTP Server, Nvidia CUDA, Computer Programming, Python (Programming Language), Linux Kernel, Machine Learning, Open Source Technology, Performance Tuning, Tensorflow, Software Engineering, Pytorch, Large Language Models, Deep Learning, cuDNN, Information Technology, ONNX (Open Neural Network Exchange) Format, SGLang, Reasoning Engines, VLLM, Model Inference, CUTLASS, MLIR (Multi-Level Intermediate Representation)
- **Published:** October 13, 2026
- **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Software-Engineer--DL-Kernel-Libraries---New-College-Grad-2027_JR2027337

## About the Role

* BS, MS, or PhD degree in Computer Science, Electrical Engineering, or related field (or equivalent experience)
 * Strong experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc) or inference engines and runtimes such as vLLM, SGLang, and MLC.
 * Strong Python and C/C++ programming skills

Ways to stand out from the crowd:

 * Background in domain specific compiler and library solutions for LLM inference and training (e.g. FlashInfer, Flash Attention)
 * Expertise in training frameworks and inference engines
 * Expertise in machine learning compilers (e.g. Apache TVM, MLIR)
 * Strong experience in GPU kernel development and performance optimizations (especially using CUDA C/C++, CUTLASS DSL, cuTile, Triton, or similar)
 * Open source project ownership or contributions

## Description

We're looking for Software Engineer Interns to help develop groundbreaking technologies in the deep learning inference and training systems software stack! We build innovative AI systems software, primarily cuDNN and FlashInfer. As a member of the team, you'll develop libraries, code generators, and GPU kernel technologies for NVIDIA's hardware architecture. This means designing and building things like new abstractions, efficient kernel implementations, and kernel code generators to accelerate large language models, agents, and other high-impact AI workloads.

What you'll be doing:

 * Innovating and developing new AI systems technologies for efficient inference and training
 * Designing, implementing, and optimizing kernels for high impact AI workloads
 * Designing and implementing extensible abstractions for serving engines and training frameworks
 * Building efficient just-in-time domain specific compilers and runtimes
 * Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries, kernels, and GPU arch teams
 * Contributing to open source communities across FlashInfer, cuDNN, vLLM, SGLang, PyTorch, JAX, and XLA