Senior System Software Engineer - Local AI
NVIDIA
Senior System Software Engineer - Local AI at NVIDIA is a full time role based in Pune, India. It was published on 25 July 2026 and was open at last check.
| Role | Senior System Software Engineer - Local AI |
|---|---|
| Company | NVIDIA |
| Location | Pune, India |
| Employment type | Full Time |
| Published | 25 July 2026 |
| Status | Open at last check |
NVIDIA has continuously reinvented itself for over two decades. The invention of the GPU in 1999 fueled the growth of PC gaming, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning has ignited modern AI, positioning NVIDIA as a leading AI computing company.
There is an increasing focus on delivering AI models locally, closer to the source of data. This reduces latency, improves real-time processing, and addresses privacy concerns by minimizing data transfer to centralized servers. As technology advances, client-side AI (local execution) will play a key role in shaping digital experiences. The LocalAI team is seeking a Senior Systems Software Engineer to build efficient on-device AI software for RTX and DGX-class systems. This role focuses on high-performance local inference, low latency, efficient memory use, infrastructure and practical deployment on resource-constrained platforms.
What you'll be doing:
Partnering with NVIDIA's software, research, architecture, and product teams to align strategies and technical needs, encouraging the ecosystem of AI on RTX and DGX PCs. Building and optimizing local AI inference stack for RTX, RTX Pro and DGX GPUs, focusing on performance, stability, and scalability across various hardware architectures. Architecture and development of modern inference runtimes and execution stacks, covering frameworks like Llama.cpp, vLLM, PyTorch, WinML, DXCGC, and TensorRT-RTX across LLMs, vision-language, TTS, ASR, and diffusion AI workloads. Perform end-to-end optimization of AI models, data pipelines, and inference runtimes to enhance performance across current and next-generation GPU architectures. Apply model optimization techniques such as quantization, pruning, sparsity, and distillation to enable efficient deployment of large models on local and edge devices. Perform system-level debugging, performance optimization, and performance–accuracy trade-off analysis; develop infrastructure for performance and accuracy sweeps, analyze results to identify gaps, and drive fixes; and establish engineering guidelines to accelerate bring-up and ensure production readiness of new models and inference backends.
What we need to see :
5+ years of experience with Bachelor's, Master's, or PhD in Computer Science, Software Engineering, Mathematics, or a related field, or equivalent experience. Excellent C++ programming and debugging skills, with a strong understanding of data structures, algorithms and machine learning. Proven experience working with AI inferencing pipelines and applications using ML/DL frameworks, such as Llama.cpp, vLLM, PyTorch, WinML, DXCGC and TensorRT. Deep interest in inference backends and runtime internals, including scheduling, memory management, KV-cache behavior, graph execution, quantization, and hardware-aware optimization. Strong analytical and problem-solving abilities, with the capability to multitask effectively in a dynamic environment. Outstanding written and oral communication skills, facilitating effective collaboration with management and engineering teams.
Ways to stand out from the crowd:
Understanding of modern techniques in Machine Learning, Deep Neural Networks, and Generative AI, with relevant contributions to major open-source projects. Consistent track record of delivering end-to-end products with geographically distributed teams in multinational product companies. Proficiency in lower-level system/GPU programming, CUDA, and developing high-performance systems. Contributions to open-source inference runtimes, model tooling, or performance infrastructure. Hands-on experience building applications with frameworks and APIs like Llama.cpp, PyTorch, TensorRT, Vulkan, and DirectX, vLLM
We're a top employer known for innovation and growth. We are an equal-opportunity employer and value diversity at our company. With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers of technology. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we would like to hear from you.
Create your free OnJob profile to apply — we'll take you to NVIDIA's application after sign-up. · Posted 25 Jul 2026.
Senior System Software Engineer - Local AI at NVIDIA — questions answered
What does the Senior System Software Engineer - Local AI role at NVIDIA pay?
NVIDIA does not publish a salary on this Senior System Software Engineer - Local AI listing, so OnJob shows no figure for it rather than an estimate. For what this role pays across the market, the OnJob salary guides aggregate the live listings that do disclose pay.
Where is the Senior System Software Engineer - Local AI role at NVIDIA based?
NVIDIA lists this Senior System Software Engineer - Local AI role in Pune, India, advertised as full time work at that location. Larger employers sometimes cover several sites under one city name, so confirm the exact office with NVIDIA before you apply.
Is the Senior System Software Engineer - Local AI role at NVIDIA still open?
The Senior System Software Engineer - Local AI posting at NVIDIA was open at OnJob's last check of the employer's careers page, having been published on 25 July 2026. OnJob re-checks source listings on each build and marks a role closed once it disappears, but listings can close without notice, so the employer's own page is the final word.
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