Senior Integration Engineer - Autonomous Vehicle

Details

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error — this is truly an extraordinary time and the era of AI has begun. Image recognition and speech recognition — GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. The GPU started out as the engine for simulating human creativity, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and AI come together in our architecture.

Our team builds NVIDIA's end-to-end autonomous driving application. We are seeking software engineers who want to work "full stack" on crafting self-driving solutions on NVIDIA's multi-computer and heterogeneous hardware architectures. We are now looking for a Senior Integration Engineer, Autonomous Vehicle.

Responsibilities

• Define functional software architecture for NVIDIA's L2/L3/L4 autonomous driving solutions.
• Integrate modular software components (e.g., perception, planning, etc.) together to implement customer-required self-driving functions.
• Optimize product implementation to achieve target performance goals.
• Diagnose system software and functional driving issues reported on target driving platforms, including on-road and simulation.
• Develop efficient mechanisms to improve utilization on computers with multiple heterogeneous hardware engines.
• Perform in-vehicle tests, collect data and complete autonomous drive missions.
• Develop system tests, document product functions, evaluate quality and propose corrective actions.
• Develop highly efficient product code in C++, making use of high algorithmic parallelism offered by GPGPU programming (CUDA).
• Follow quality and safety standards such as defined by MISRA.

Requirements

• BS/MS or higher in computer engineering, computer science or related engineering fields, or equivalent experience.
• 5+ years of relevant industry experience.
• Excellent C and C++ programming skills.
• Experience developing and debugging multithreaded/distributed applications (e.g., multimedia systems, game engines). Profound knowledge of programming and debugging techniques.
• Experience developing software for heterogeneous architectures, including GPUs.
• Knowledge of image processing APIs (e.g., OpenCV) and MATLAB tools; experience with automotive systems, notably ADAS applications.
• Software development experience for CUDA, Linux, and QNX.
• Experience with version control systems (GIT) and build systems such as CMake and Bazel.
• Hands-on, team-oriented, detail-oriented with strong data organization and presentation skills.
• Solid understanding of Linux, Android, and/or other real-time operating systems.

Ways to stand out

• Understanding of parallel, embedded and distributed architectures.
• Thrives on writing low-latency, highly performant code.
• Great communication and analytical skills.
• Self-motivated and a great teammate.

Benefits

• Base salary will be determined based on your location, experience, and the pay of employees in similar positions.
• Base salary range: 148,000 USD - 235,750 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
• Eligible for equity and additional benefits (see company benefits page).
• NVIDIA is an equal opportunity employer and fosters a diverse work environment.

Application details

• Applications for this job will be accepted at least until August 1, 2025.