Senior Integration Engineer, End-to-End Model - Autonomous Vehicles

Details

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. The team develops NVIDIA’s end-to-end autonomous driving application. The Senior Integration Engineer will accelerate the development, integration, evaluation, and deployment of end-to-end driving models across large-scale training infrastructure, simulation environments, and production vehicle platforms. This role works across model development, data, simulation, systems software, and vehicle engineering to turn evolving AI models into reliable, high-performance autonomous driving functionality on NVIDIA’s heterogeneous computing platforms.

Responsibilities

• Integrate learned driving models with vehicle interfaces, sensor inputs, localization, mapping, safety systems, and other autonomous driving components.
• Establish model input, output, timing, state-management, and runtime interface contracts.
• Partner with model developers to improve model quality, debuggability, runtime behavior, and deployment readiness.
• 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, with experience in model inference technologies such as CUDA and TensorRT.
• Proficiency in Python and experience 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.

Preferred Qualifications

• 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.

Compensation and Benefits

The base salary range is USD 152,000–241,500 for Level 3 and USD 184,000–287,500 for Level 4. Base salary is determined by location, experience, and the pay of employees in similar positions. The role also includes eligibility for equity and benefits.

Applications will be accepted at least until September 22, 2026. NVIDIA is an equal opportunity employer.