We are now looking for a Computer Vision Engineer - Autonomous Vehicles - New College Graduate:
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 is building the Map Perception component of the NVIDIA DriveWorks SDK, with the goal to build a scalable crowd-sourced mapping platform for autonomous driving, that will enable a fleet of autonomous vehicles to create and consume map data collaboratively.
We are seeking software engineers with interests in computer vision, mapping, LiDAR perception, deep learning, sensor fusion, and other related areas, to work as part of NVIDIA’s autonomous vehicles team.
What You'll Be Doing:
- Taking algorithms from initial evaluation and experimentation all the way to shipping them as part of the NVIDIA DriveWorks SDK and related products.
- Developing and optimizing software architecture for real-world performance while matching or exceeding customer requirements.
- Working on areas such as sensor self-calibration, vehicle ego-motion, perception, mapping and localization using a variety of sensor modalities (Camera, LiDAR, Radar, INS, GPS, Odometry, etc.).
- Collecting map data, working on storage systems, fusing and mining data, integrating into a cloud-based service.
- Solidifying existing algorithms, and working with large amounts of real and synthetic data to continuously improve the algorithmic and computational performance.
- Performing in-vehicle tests, capturing data and completing autonomous drive missions.
- 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). Code written must comply to strict quality and safety standards such as defined by MISRA.
What We Need To See:
- MS degree in Computer Science, Robotics, or related field.
- To be successful you should have experience in one or more of the following areas: Computer vision, visual geometry, LIDAR perception, SLAM and/or deep learning.
- Experience building robust software.
- Have strong programming and debugging skills in C++ and real-time multi-threaded software development.
- Good communications and analytical skills. Ability to work with multiple cross-functional teams across multiple time zones.
Ways To Stand Out From The Crowd:
- Experience developing real-time LIDAR Perception and/or Computer Vision systems and / or scalable cloud based mapping solutions.
- Experience fusing data from different sensor modalities (e.g. Images and LIDAR data) to enable information conflation, label propagation, cross training for deep learning.
- Experience with visual geometry and deep learning in a shipping product context.
- Software development on embedded platforms or large scale cloud services.
- Experience with GPGPU programming (CUDA and OpenCL).
We believe that realizing self-driving cars will be a defining contribution of our generation (e.g. traffic accidents are responsible for ~1.25 million deaths per year world-wide). We have the funding and scale, but we need your help on our team.
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.