Deep Learning Software Engineer, TensorRT Performance - New College Grad 2026

About the role

NVIDIA is seeking an experienced Deep Learning Software Engineer passionate about analyzing and improving the performance of NVIDIA’s inference ecosystem. The role involves working on GPU-accelerated deep learning inference software like TensorRT, DL benchmarking software, and performingant solutions to deploy and serve these models. Collaboration with diverse teams is essential.

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 and collaborate with a diverse set of teams involving workflow improvements, performance modeling, performance analysis, kernel development and inference software development.
• Scale performance of deep learning models across different architectures and types of NVIDIA accelerators.

Requirements

• 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.

Qualifications

• 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).
• Experience optimizing performance for low-latency, resource-constrained systems or embedded AI pipelines (e.g. Jetson systems or other edge AI accelerators).

Skills

• GPU deep learning.

Benefits

• Competitive base salary ranging from $124,000 - $195,500 for Level 2 and $152,000 - $241,500 for Level 3.
• Eligibility for equity and benefits.

Pay

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 - $195,500 for Level 2 and $152,000 - $241,500 for Level 3.

Schedule

Full-time position.