NVIDIA seeks a Senior Software Engineer specializing in Deep Learning Inference for our growing team. As a key contributor, you will help design, build, and optimize the GPU-accelerated software that powers today’s most sophisticated AI applications. Our team is responsible for developing and maintaining high-performance deep learning frameworks, including SGLang and vLLM, which are at the forefront of efficient large-scale model serving and inference. You will play a central role in improving these platforms, facilitating smooth deployment and serving of groundbreaking language models.
You’ll work closely with the deep learning community to implement the latest algorithms for public release in frameworks like SGLang and vLLM, as well as other DL frameworks. Your work will focus 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'll bring to bear open-source tools and plugins—including CUTLASS, OAI Triton, NCCL, and CUDA kernels—to implement and optimize model serving pipelines.
What you'll be doing:
Performance optimization, analysis, and tuning of DL models in various 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, vLLM and SGLang, FlashInfer and LLM software solutions.
Work with cross-collaborative teams across frameworks, NVIDIA libraries and inference optimization innovative solutions.
What we need to see:
Masters or PhD or equivalent experience in relevant field (Computer Engineering, Computer Science, EECS, AI).
6+ years of relevant software development experience.
Excellent C/C++ programming and software design skills. SW Agile skills are helpful and Python experience is a plus.
Prior experience with training, deploying or optimizing the 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.
Ways to stand out from the crowd:
Contribute to Deep Learning Software projects, such as PyTorch, vLLM, and SGLang to drive advancements in the field.
Experience with Multi-GPU Communications (NCCL, NVSHMEM)
Experience building and shipping products to enterprise customers.
GPU programming experience (CUDA, OAI TRITON or CUTLASS).
NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: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.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.Skills Required
- Master’s degree, PhD, or equivalent experience in Computer Engineering, Computer Science, EECS, AI, or a relevant field
- 6+ years of relevant software development experience
- Excellent C/C++ programming and software design skills
- Software Agile skills
- Python experience
- Experience training, deploying, or optimizing deep learning model inference in production
- Experience with performance modeling, profiling, debugging, and code optimization
- Architectural knowledge of CPUs and GPUs
- Contributions to deep learning software projects such as PyTorch, vLLM, or SGLang
- Experience with multi-GPU communications, including NCCL or NVSHMEM
- Experience building and shipping products to enterprise customers
- GPU programming experience with CUDA, OAI Triton, or CUTLASS
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
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Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
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Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
