> Markdown version of [/jobs/ext/4344062-ai-application-developer-gpu-and-soc-architecture-modeling](https://www.wearedevelopers.com/jobs/ext/4344062-ai-application-developer-gpu-and-soc-architecture-modeling). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Application Developer - GPU and SOC Architecture Modeling - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, United States - **Experience:** Expert - **Salary:** $152,000 - $241,500 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, C++ (Programming Language), Computer Engineering, Software Debugging, Python (Programming Language), Tensorflow, LangChain, Large Language Models, Generative AI, Agentic-AI, LangSmith, Information Technology, Claude, Agent SDK, GPT - **Published:** October 16, 2026 - **Apply:** https://startup.jobs/senior-ai-application-developer-gpu-and-soc-architecture-modeling-2100-nvidia-usa-10476735 ## About the Role * BS, MS, PhD or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a related field with 5+ years of experience in related areas * Proficiency in C++, Python and ML frameworks like LangChain, LangSmith, Claude Agent SDK, Nemo Agent Toolkit, or other AI agentic tools * Hands-on experience with LLMs (e.g. GPT, Claude, Llama) and multimodal models * Background in Computer Architecture with experience in modeling is a plus * Strong collaboration skills with design and engineering teams * Strong problem-solving and debugging skills, with a track record of driving issues to closure ## Description * Develop and deploy scalable GenAI applications that integrate with existing workflows and enhance overall productivity * Use state-of-the-art AI tools and techniques to accelerate GPU/ SOC Architecture modeling * Work with hardware architects to identify how to best design, customize, and deploy AI-based solutions to their specific problem domains. * Collaborate with infrastructure engineers to improve existing automated workflows by incorporating LLMs and establishing best practices for future solutions. * Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge.