Used Tools & Technologies
GenAIRequired Skills & Competences
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.
Software Development @ 6
Python @ 4
Machine Learning @ 4
Communication @ 7
Rust @ 7
LLM @ 4
PyTorch @ 4
CUDA @ 4
GPU @ 6
Deep Learning @ 4
Generative AI @ 4
AI @ 4
vLLM @ 4
OpenCL @ 4
TensorRT @ 4
SGLang @ 4
Performance Analysis @ 4
JAX @ 4
- 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
At NVIDIA, we're at the forefront of innovation, driving advancements in AI and machine learning to solve some of the world’s most challenging problems. The TensorRT team develops industry-leading deep learning inference software for NVIDIA AI accelerators. As a Senior Software Engineer in the TensorRT team, you will design and implement inference software optimizations to power AI applications on NVIDIA GPUs.
Responsibilities
- Design, develop and optimize NVIDIA TensorRT and TensorRT-LLM to accelerate inference applications for datacenter, workstations, and PCs.
- Develop software in C++, Python, and CUDA for seamless and efficient deployment of state-of-the-art LLMs and Generative AI models.
- Collaborate with deep learning experts and GPU architects across the company to influence hardware and software design for inference.
Requirements
- BS, MS, PhD or equivalent experience in Computer Science, Computer Engineering or a related field.
- 4+ years of software development experience on a large codebase or project.
- Strong proficiency in C++ (required); experience with Rust or Python is also noted.
- Experience in developing deep learning frameworks, compilers, or system software.
- Excellent problem-solving skills and the ability to learn and work effectively in a fast-paced, collaborative environment.
- Strong communication skills and the ability to articulate complex technical concepts.
Ways to stand out
- Experience in developing inference backends and compilers for GPUs.
- Knowledge of machine learning techniques and GPU programming with CUDA or OpenCL.
- Background working with LLM inference frameworks like TensorRT-LLM, vLLM, SGLang.
- Experience with deep learning frameworks such as TensorRT, PyTorch, JAX.
- Knowledge of close-to-metal performance analysis, optimization techniques, and tools.
Compensation
- Base salary range (Level 3): 152,000 USD - 241,500 USD per year.
- Base salary range (Level 4): 184,000 USD - 287,500 USD per year.
- You will also be eligible for equity and benefits.
Additional information
- #LI-Hybrid
- Applications for this job will be accepted at least until April 14, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.