We are now looking for a Senior Application Software Engineer, Autonomous Vehicles.
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 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.
What you will be doing:
What we need to see in you:
Defining functional software architecture NVIDIA's L2/L3/L4 autonomous driving solutions.
Integrating modular software components (e.g. perception, planning, etc.) together to implement customer-required self-driving functions.
Optimizing product implementation to achieve target performance goals.
Diagnosing system software & functional driving issues reported on our target driving platforms, including on-road & simulation.
Developing efficient mechanisms to improve utilization on computers with multiple heterogeneous hardware engines.
Performing in-vehicle tests, collecting data and completing autonomous drive missions.
Developing system tests, documentation of product functions, 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.
Ways you can stand out from the crowd:
BS/MS or higher in computer engineering, computer science or related engineering fields, or equivalent experience.
Prefer 5+ years of relevant industry experience.
Excellent C and C++ programming skills.
Experience developing and debugging multithreaded/distributed applications like multimedia systems, game engines, etc.
Profound knowledge of programming and debugging techniques, especially for parallel and distributed architectures.
Solid understanding on Linux, Android, and/or other real-time operating systems.
Hands-on experience with frameworks for robotics such as ROS and/or for multimedia such as GStreamer.
Thrive on writing low latency, highly performant code.
Great communication and analytical skills.
Self-motivated and a great teammate.
Understanding of embedded architectures.
Experience on developing software in heterogeneous architectures, including GPUs.
Knowledge of image processing APIs (e.g. OpenCV) and MATLAB tools.
Knowledge of automotive systems, notably ADAS applications.
Software development for CUDA and Linux.
Experience with version control systems GIT and build system like CMake/Bazel.
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.