Deep Learning Senior Engineer, End-To-End Autonomous Driving
NVIDIA· Engineer, Sys SW
Shanghai, BeijingunknownPosted 4mo ago
About the role
Senior engineer to design, implement, and deploy end-to-end autonomous driving systems running on NVIDIA chips in mass-production vehicles, leveraging AI 2.0 concepts (LLMs, VLMs, VLAs) for enhanced reasoning, planning, and interactivity in autonomous robotics.
Responsibilities
- Design and train innovative large-scale models—including generative, imitation, and reinforcement learning—to improve the planning and reasoning capabilities of driving systems.
- Build, pre-train, and fine-tune LLM/VLM/VLA systems for deployment in real-world autonomous driving and robotics applications.
- Explore novel data generation and collection strategies to improve diversity and quality of training datasets.
- Collaborate with cross-functional teams to deploy AI models in production environments, ensuring performance, safety, and reliability standards are met.
- Integrate machine learning models directly with vehicle firmware to deliver production-quality, safety-critical software.
Qualifications
- Hands-on experience building LLMs, VLMs, or VLAs from scratch or proven track record as a top-tier coder in autonomous systems.
- Deep understanding of modern deep learning architectures and optimization techniques.
- Proven record of deploying production-grade ML models for self-driving, robotics, or related fields at scale.
- Strong programming skills in Python and proficiency with major deep learning frameworks.
- Familiarity with C++ for model deployment and integration in safety-critical systems.
- PhD with 2+ years, MS (or equivalent experience) with 4+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
Skills
Required:LLMsVLMsVLAsDeep LearningPython
Nice to have:C++
Last updated Sep 4, 2026. Interested? Apply on the company site.
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