Deep Learning Software Engineer, TensorRT Performance - New College Grad 2027

NVIDIA; United States; On-site; USD 124,000 - 196,000; Full time

Benefits offered by this job

Equity

Job summary

NVIDIA is seeking a Deep Learning Software Engineer focused on TensorRT performance to analyze and improve the inference ecosystem. You will contribute to optimization and benchmarking across TensorRT, Torch-TensorRT, and related tools, collaborating with teams across AI, automotive, and robotics.

The role requires strong C++/Python, experience with DL frameworks, and a proven ability to drive performance improvements. Base salary varies by level and location, with equity and benefits included.

Qualifications

• 2 years of relevant software development experience.
• Strong C++ and Python programming skills.
• Experience with DL frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX) and inference libraries (e.g. TensorRT, TensorRT-LLM, vLLM, SGLang, FlashInfer).
• Experience with performance analysis and performance optimization.

Responsibilities

• Establish groundbreaking performance benchmarking methodologies and analysis workflows and identify performance issues and opportunities for NVIDIA's inference ecosystem (e.g. TensorRT/TensorRT-EdgeLLM/Torch-TensorRT).
• Contribute features and code to NVIDIA/OSS inference frameworks including but not limited to TensorRT/TensorRT-EdgeLLM/Torch-TensorRT.
• Develop new model pipelines for NVIDIA's inference ecosystem with optimized performance including but not limited to areas like quantization, scheduling, memory management, and distributed inference to set the gold standard for Gen AI performance.
• Work with cross-collaborative teams inside and outside of NVIDIA across generative AI, automotive, robotics, image understanding, and speech understanding to set directions and develop innovative inference solutions.
• Scale performance of deep learning models across different architectures and types of NVIDIA accelerators.

Skills

C++

Python

Performance analysis

Deep learning concepts

Education

Bachelor's degree

Master's degree

PhD

Tools

TensorRT

TensorRT-LLM

Torch-TensorRT

vLLM

SGLang

FlashInfer

CUDA

PyTorch

JAX

TensorFlow

ONNX

TileIR

CuTeDSL

Cutlass

Triton

Job description

We are now looking for a Deep Learning Software Engineer, TensorRT Performance! NVIDIA is seeking an experienced Deep Learning Engineer passionate about analyzing and improving the performance of NVIDIA's inference ecosystem! NVIDIA is rapidly growing our research and development for Deep Learning Inference and is seeking excellent Software Engineers at all levels of expertise to join our team. Companies around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in areas like Generative AI, Recommenders and Vision that have put DL into every software solution. Join the team that builds the software to enable the performance optimization, deployment and serving of these DL inference solutions. We specialize in developing GPU-accelerated deep learning inference software like TensorRT, DL benchmarking software and performant solutions to deploy and serve these models.

What you'll be doing:

• Establish groundbreaking performance benchmarking methodologies and analysis workflows and identify performance issues and opportunities for NVIDIA's inference ecosystem (e.g. TensorRT/TensorRT-EdgeLLM/Torch-TensorRT)
• Contribute features and code to NVIDIA/OSS inference frameworks including but not limited to TensorRT/TensorRT-EdgeLLM/Torch-TensorRT.
• Develop new model pipelines for NVIDIA's inference ecosystem with optimized performance including but not limited to areas like quantization, scheduling, memory management, and distributed inference to set the gold standard for Gen AI performance.
• Work with cross-collaborative teams inside and outside of NVIDIA across generative AI, automotive, robotics, image understanding, and speech understanding to set directions and develop innovative inference solutions.
• Scale performance of deep learning models across different architectures and types of NVIDIA accelerators.

What we need to see:

• Bachelors, Masters, PhD, or equivalent experience in relevant fields (Computer Science, Computer Engineering, EECS, AI).
• 2 years of relevant software development experience.
• Strong C++, Python programming and software engineering skills
• Experience with DL frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX) and inference libraries (e.g. TensorRT, TensorRT-LLM, vLLM, SGLang, FlashInfer).
• Experience with performance analysis and performance optimization

Ways to stand out from the crowd:

• Strong foundation and architectural knowledge of GPUs.
• Deep understanding of modern deep learning models and workloads (e.g. Transformers, Recommenders, ASR, TTS, Visual Understanding).
• Proficiency in one of the deep learning programming domain specific languages (e.g. CUDA/TileIR/CuTeDSL/cutlass/Triton).
• Prior contributions to major LLM inference frameworks (e.g. vLLM) or prior experience with graph compilers in deep learning inference (e.g. TorchDynamo/TorchInductor).
• Prior experience optimizing performance for low-latency, resource-constrained systems or embedded AI pipelines (e.g. Jetson systems or other edge AI accelerators).

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 .

Applications for this job will be accepted at least until October 16, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA