Senior Integration Engineer

We are seeking a Senior Integration Engineer to work on NVIDIA's end-to-end autonomous driving application. You will accelerate the development, integration, evaluation, and deployment of driving models across large-scale training infrastructure, simulation environments, and production vehicle platforms.

Responsibilities:

• 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.

Requirements:

• 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.

Nice to Have:

• 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.

The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.