> Markdown version of [/jobs/ext/3000550-senior-integration-engineer-end-to-end-model-autonomous-vehicles](https://www.wearedevelopers.com/jobs/ext/3000550-senior-integration-engineer-end-to-end-model-autonomous-vehicles). 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). --- # Senior Integration Engineer, End-to-End Model - Autonomous Vehicles - **Company:** NVIDIA Corporation - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $152,000.0 - $241,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Software Applications, Computing Platforms, C++ (Programming Language), Program Optimization, Nvidia CUDA, Computer Engineering, Software Debugging, Linux, Middleware, Python (Programming Language), Machine Learning, Network Planning and Design, Software Architecture, Real-Time Operating Systems, Software Engineering, Pytorch, Information Technology, Production Code, TensorRT - **Published:** September 19, 2026 - **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Integration-Engineer--End-to-End-Model---Autonomous-Vehicles_JR2025038 ## About the Role * PhD with 1+ year, MS with 3+ years, or BS (or equivalent experience) with 5+ years of relevant experience in Computer Science, Computer Engineering, Robotics, Machine Learning, or a related field. * Strong C++ programming, software architecture, debugging, and performance-analysis skills, and model inference technologies such as CUDA and TensorRT. * Proficiency in Python and experience working with modern machine-learning frameworks such as PyTorch. * Experience developing software on Linux and embedded or real-time operating systems such as QNX. * Experience integrating machine-learning models into complex, performance-sensitive production systems. * Ability to diagnose issues across model behavior, application software, middleware, operating systems, and hardware. * Experience with autonomous driving, robotics, ADAS, or another real-time intelligent system. Ways to stand out from the crowd: * Experience deploying end-to-end driving, robotics, or embodied-AI models on production hardware. * Familiarity with model optimization, quantization, compilation, profiling, and hardware-aware neural-network design. * A track record of turning research models into robust, measurable, and maintainable product functionality. * Self-motivation, sound engineering judgment, and a passion for solving cross-functional integration challenges. ## Description Intelligent machines powered by artificial intelligence are transforming transportation. NVIDIA is building the computing platforms, software, and AI systems that enable autonomous vehicles to perceive, reason, and act in complex environments. Our team develops NVIDIA's end-to-end autonomous driving application. We are looking for a Senior Integration Engineer to accelerate the development, integration, evaluation, and deployment of end-to-end driving models across large-scale training infrastructure, simulation environments, and production vehicle platforms. In this role, you will work across model development, data, simulation, systems software, and vehicle engineering. You will help turn rapidly evolving AI models into reliable, high-performance autonomous driving functionality running on NVIDIA's heterogeneous computing platforms. What you'll be doing: * Integrate learned driving models with vehicle interfaces, sensor inputs, localization, mapping, safety systems, and other autonomous driving components. * Establish clear model input, output, timing, state-management, and runtime interface contracts. * Partner with model developers to improve model quality, debuggability, runtime behavior, and readiness for deployment. * Investigate discrepancies between model behavior in development environments and on target vehicle platforms. * Optimize model inference and surrounding software to meet latency, throughput, memory, determinism, and power requirements. * Develop tools and metrics for evaluating driving quality, safety, robustness, and regression performance at scale. * Perform in-vehicle testing, collect and analyze driving data, and complete autonomous driving missions. * Develop high-quality production code in C++ and Python using CUDA and other GPU-accelerated technologies. ## 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) - [Developing an AI.SDK](https://www.wearedevelopers.com/videos/198-developing-an-ai-sdk) - [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) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [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 software is steering vehicle technology](https://www.wearedevelopers.com/magazine/515-how-software-is-steering-vehicle-technology) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)