Software Tools Engineer Manager, Autonomous Vehicles


April 19, 2021

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. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as “the AI computing company.” Make the choice to join us today.
Our team builds the NVIDIA DriveWorks SDK with the goal to provide a scalable software stack and framework to build autonomous vehicles. We are seeking a hands-on lead senior engineer with interests in designing, developing and maintaining SDK tools to improve the usability of the system and the developer experience for the developers and users of the autonomous driving stack.
What you will be doing:

  • Leading a team of engineers designing and developing command line and graphical tools used to manipulate and visualize data, debug and develop applications.

  • Working on areas such as in-car, desktop and cloud workflows to improve developer experiences.

  • Solidifying existing tools to provide a comprehensive toolchain starting from sensor tools, data collection, algorithm development and verification, cloud-based AI training systems and data visualization.

  • Performing in-vehicle tests and working with developers to improve their flows.

  • Developing unit tests, documentation for features, evaluating quality and proposing corrective actions.

  • Developing 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.

What we need to see:

  • BS/MS (or equivalent experience) or higher in computer engineering, computer science or related engineering disciplines.

  • Prefer 5+ years of relevant industry experience.

  • 5+ years of team Lead or team management experience.

  • Excellent C and C++ programming skills.

  • Experience developing and debugging multithreaded/distributed applications like multimedia systems, game engines, etc.

  • Strong knowledge of programming and debugging techniques, especially for parallel and distributed architectures.

  • Strong knowledge on Linux, Android, and/or other real-time operating systems.

  • Great communication and analytical skills.

  • Self-motivated and a great teammate.

Ways to stand out from the crowd:

  • Understanding of embedded architectures.

  • Experience with data-parallel and/or GPGPU programming, CUDA, OpenCL.

  • Knowledge of image processing APIs (e.g. OpenCV) and MATLAB tools.

  • Software development for modern OpenGL (Core Profile) and Linux.

  • Experience developing graphical tools.

  • Background with version control systems GIT and Bazel build system.

  • Be hands-on and work well within a team of algorithm, software and hardware engineers, with a significant level of detail orientation and a penchant for data organization and presentation.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression , sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.