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Nvidia Senior SLAM Deep Learning Engineer Autonomous Vehicles 
China, Beijing, Beijing 
322103618

Today
China, Beijing
China, Shanghai
time type
Full time
posted on
Posted 5 Days Ago
job requisition id

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.