Deep Learning Software Engineer, Inference - New College Grad 2026
Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
Agile @ 3
Algorithms
CUDA @ 1
Deep Learning @ 3
GPU @ 3
GenAI
Generative AI
LLM
NCCL @ 3
Performance Optimization @ 3
Profiling @ 3
PyTorch @ 3
Python @ 1
SGLang @ 3
Software Development @ 3
vLLM @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA seeks a Software Engineer specializing in Deep Learning Inference for its growing team. In this role, you will help design, build, and optimize GPU-accelerated software that powers sophisticated AI applications.
Our team develops and maintains high-performance open-source frameworks for efficient large-scale model serving and inference. You will help improve these platforms, facilitating smooth deployment and serving of language models.
You will work closely with the deep learning community to implement the latest algorithms for public release in inference frameworks. Your work focuses on identifying and driving performance improvements for state-of-the-art LLM and Generative AI models across NVIDIA accelerators, from datacenter GPUs to edge SoCs. You will use open-source tools and plugins—including CUTLASS, OAI Triton, NCCL, and CUDA kernels—to implement and optimize model serving pipelines.
Responsibilities
- Performance optimization, analysis, and tuning of DL models in domains like LLM, Multimodal and Generative AI.
- Scale performance of DL models across different architectures and types of NVIDIA accelerators.
- Contribute features and code to NVIDIA’s inference libraries and solutions, including vLLM and SGLang, FlashInfer, and other LLM software solutions.
- Work with cross-collaborative teams across frameworks, NVIDIA libraries, and inference optimization for innovative solutions.
Requirements
- Pursuing or recently completed a MS or PhD in Computer Engineering, Computer Science, EECS, AI or related field, or equivalent experience.
- Software development experience.
- Excellent C/C++ programming and software design skills; SW Agile skills are helpful.
- Python experience is a plus.
- Prior experience with training, deploying, or optimizing inference of DL models in production is a plus.
- Prior background with performance modeling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU is a plus.
- GPU programming experience (CUDA, OAI Triton or CUTLASS) is a plus.
Ways to stand out:
- Contribute to deep learning software projects, such as PyTorch, vLLM, and SGLang.
- Experience with Multi GPU Communications (NCCL, NVSHMEM).
Salary
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.
You will also be eligible for equity and benefits.