Senior Deep Learning Software Engineer, LLM Performance at NVIDIA

You are a seasoned software engineer with at least eight years of experience and a degree in a technical field like Computer Science or AI. You have mastered C,

Work type: hybrid

Location: US, CA, Santa Clara

Salary: $184,000 – $356,500/yr

Type: Full-time

Summary

You are a seasoned software engineer with at least eight years of experience and a degree in a technical field like Computer Science or AI. You have mastered C, C++, and Python and possess deep expertise in optimizing performance for large-scale deep learning models. **What makes it worth a look...** NVIDIA is hiring for this hybrid role in Santa Clara with an annual base salary range between $184,000 and $356,500 depending on your level. You will work on cutting-edge inference frameworks for Generative AI and Large Language Models alongside a world-class team. **You might be a good fit if you...** * Have hands-on experience with TensorRT, VLLM, or Triton. * Can demonstrate proficiency in CUDA or GPU-based programming. * Possess deep knowledge of deep learning frameworks such as PyTorch or JAX. * Understand how to optimize model throughput and latency for modern GPU architectures.

Job Description

We are now looking for a Senior Deep Learning Software Engineer, LLM Performance! NVIDIA is seeking an experienced Deep Learning Engineer passionate about analyzing and improving the performance of LLM inference! 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 LLM, 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 solutions. We specialize in developing GPU-accelerated Deep learning software like TensorRT, DL benchmarking software and performant solutions to deploy and serve these models.

Collaborate with the deep learning community to implement the latest algorithms for public release in TensorRT LLM, VLLM, SGLang and LLM benchmarks. Identify performance opportunities and optimize SoTA LLM models across the spectrum of NVIDIA accelerators, from datacenter GPUs to edge SoCs. Implement LLM inference, serving and deployment algorithms and optimizations using TensorRT LLM, VLLM, SGLang, Triton and CUDA kernels. Work and collaborate with a diverse set of teams involving performance modeling, performance analysis, kernel development and inference software development.

What you'll be doing:

Performance optimization, analysis, and tuning of LLM, VLM and GenAI models for DL inference, serving and deployment in NVIDIA/OSS LLM frameworks.

Scale performance of LLM models across different architectures and types of NVIDIA accelerators.

Scale performance for max throughput, minimum latency and throughput under latency constraints.

Contribute features and code to NVIDIA/OSS LLM frameworks, inference benchmarking frameworks, TensorRT, and Triton.

Work with cross-collaborative teams across generative AI, automotive, image understanding, and speech understanding to develop innovative solutions.

What we need to see:

Bachelors, Masters, PhD, or equivalent experience in relevant fields (Computer Engineering, Computer Science, EECS, AI).

At least 8 years of relevant software development experience.

Excellent Python/C/C++ programming, software design and software engineering skills

Experience with a DL framework like PyTorch, JAX, TensorFlow.

Ways to stand out from the crowd:

Prior experience with a LLM framework or a DL compiler in inference, deployment, algorithms, or implementation

Prior experience with performance modeling, profiling, debug, and code optimization of a DL/HPC/high-performance application

Architectural knowledge of CPU and GPU

GPU programming experience (CUDA or OpenCL)

GPU deep learning has provided the foundation for machines to learn, perceive, reason and solve problems posed using human language. The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for deep learning, and NVIDIA is increasingly known as “the AI computing company.” Come, join our DL Architecture team, where you can help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field.

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and [benefits](https://www.nvidia.com/en-us/benefits/).

Applications for this job will be accepted at least until April 20, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

View this job on nocollar jobs