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

NVIDIA· Engineer, Sys SW
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Santa Clara, CA$152k - $241.5kfull-timePosted 4w ago

About the role

Senior Integration Engineer to accelerate development, integration, evaluation, and deployment of end-to-end driving models across large-scale training infrastructure, simulation environments, and production vehicle platforms for NVIDIA’s autonomous driving applications.

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.

Qualifications

  • 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.

Skills

Required:C++ programmingCUDA and TensorRTPythonPyTorchLinux / embedded RTOS (QNX)Model integrationAutonomous driving / robotics

Benefits

  • You will also be eligible for equity and benefits.
Last updated Sep 25, 2026. Interested? Apply on the company site.

About NVIDIA

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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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