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 open-source frameworks, 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 inference 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).
5+ years of relevant software development experience.
You'll need 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.
GPU programming experience (CUDA, OAI TRITON or CUTLASS) 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)
With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our special engineering teams are growing fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.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
- Masters or PhD or equivalent experience in Computer Engineering, Computer Science, EECS, or AI
- 5+ years of relevant software development experience
- Excellent C/C++ programming and software design skills
- Python experience
- Prior experience with training, deploying, or optimizing DL model inference in production
- Background in performance modeling, profiling, debugging, and CPU/GPU architecture knowledge
- GPU programming experience (CUDA, Triton or CUTLASS)
- Experience with multi‑GPU communications (NCCL, NVSHMEM)
- Familiarity with agile software practices
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 — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
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.”

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