NVIDIA has continuously reinvented itself over two decades. NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. This is our life’s work — to amplify human imagination and intelligence.
We are seeking a systems software expert with strong expertise in SLAM and deep learning for autonomous vehicles, based in Beijing or Shanghai. The ideal candidate will analyze and resolve sensor calibration and SLAM issues throughout the vehicle delivery process. This includes triaging and fixing in-platform and online problems with SLAM and sensor calibration for sensors like cameras, radars, lidars, GNSS, IMU, and CAN odometry. You will also collaborate with the team to design, implement, and deploy advanced end-to-end autonomous driving systems on NVIDIA DRIVE platform in mass-production vehicles. This work leverages LLMs, VLMs, and VLAs to deliver groundbreaking reasoning, planning, and interactivity for autonomous vehicles. Let's build the future of autonomy—together.
What you will be doing:
Investigate and resolve sensor calibration and egomotion algorithm/toolchain issues across multiple OEM vehicle platforms.
Develop core autonomous driving functionality for global markets by fusing state-of-the-art perception DNNs with map signals.
Build real-time 3D world models for planning, integrating diverse inputs from sensors and external sources.
Develop and optimize LLM, VLM, and VLA systems for autonomous driving applications, including pre-training and fine-tuning.
Design innovative data generation and collection strategies to improve dataset diversity and quality.
Collaborate with cross-functional teams to deploy end-to-end AI models in production, ensuring performance, safety, and reliability standards are met.
What we need to see:
A MS, or PhD, or equivalent professional experience in Computer Science, Computer Engineering, Mathematics, Physics, or a related discipline.
Over 3 years of relevant industry experience.
Expertise in C/C++ programming, with a comprehensive understanding of standard C++ features, algorithms, and data structures, along with proficiency in Linux environments.
In-depth knowledge of parameter models for sensor calibration.
A solid grasp of digital image processing, three-dimensional multi-view geometry, nonlinear optimization, and KF/EKF.
A robust mathematical foundation, especially in matrix-related concepts.
Engineering expertise in developing and delivering deep learning applications for autonomous vehicles or robotics
Engineering expertise in developing and delivering real-time 3D world models for planning in AV system.
Excellent collaboration skills and the ability to work effectively with individuals from various nationalities and locations.
Ways to stand out from the crowd:
Experience with a range of sensors and their data (camera, lidar, radar, IMU, GNSS, CAN Odometry).
Extensive experience in SLAM algorithms
Extensive deep learning experience related to autonomous driving.
A track record of designing SLAM algorithms for successful ADAS projects.