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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer - Local AI - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $152,000.0 - $241,500.0 - **Contract:** Permanent contract - **Skills:** Microsoft Windows, Application Programming Interfaces (APIs), Artificial Intelligence, Artificial Neural Networks, C++ (Programming Language), Program Optimization, Nvidia CUDA, Data Structures, Software Debugging, Linux, DirectX (Software), Web Browsers, Machine Learning, Smart Devices, Software Engineering, Pytorch, Software Application Programming, Generative AI, Gpu Programming, Information Technology, ONNX (Open Neural Network Exchange) Format, TensorRT, Vulkan Graphics API, Data Pipelines - **Published:** July 29, 2026 - **Apply:** https://www.disabledperson.com/jobs/73912879-senior-software-engineer-local-ai ## About the Role * 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 and algorithms. * 5+ years of experience with proficiency in AI inferencing pipelines and applications using ML/DL frameworks, including ONNX RT, PyTorch, Tensor RT, llama.cpp and vLLM. * Strong analytical and problem-solving abilities, with the ability to multitask effectively in a dynamic environment. * Outstanding written and oral communication skills enabling effective collaboration with management and engineering teams. Ways To Stand Out from The Crowd: * Understanding modern techniques in Machine Learning, Deep Neural Networks, and Generative AI with relevant contributions to major open-source projects will be a plus. * 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, developing high-performance systems. * Hands-on experience with building applications using APIs like ONNX RT, DirectX, PyTorch, TensorRT, Vulkan, llama.cpp. ## Description Local AI seeks a Senior Systems Software Engineer interested in solving client-side AI challenges on Windows and Linux PCs with limited resources. What You'll Be Doing: * Partnering with NVIDIA software, research, architecture, and product teams to align strategies and technical needs for fostering the ecosystem of AI on RTX and DGX PCs. * Collaborate closely with industry partners to advance AI across critical domains-including graphics, web browsers, and edge devices-by driving innovation in both open and closed source technologies with emphasis on system level support. * Improving performance on current and next-generation GPU architectures by conducting in-depth analysis and end-to-end optimization of AI models, data processing pipelines, and inference runtime features. * Identifying, evaluating, and implementing compute and memory optimization techniques-such as quantization, distillation, and pruning-for large AI models; fine-tuning and compressing models to fit edge devices. ## Related Videos - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Trends, Challenges and Best Practices for AI at the Edge](https://www.wearedevelopers.com/videos/630-trends-challenges-and-best-practices-for-ai-at-the-edge) - [Efficient deployment and inference of GPU-accelerated LLMs​](https://www.wearedevelopers.com/videos/929-efficient-deployment-and-inference-of-gpu-accelerated-llms) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)