Senior Autonomous Driving Systems Engineer

NVIDIA; United States; On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is developing the next generation of AI-native autonomous driving systems in the United States. You will contribute to end-to-end autonomous driving architectures spanning perception through control and model inference, with emphasis on safety, scalability, and integration of research into production.

You will collaborate across research and engineering teams, shaping system architecture from 0 to scale while applying knowledge of CUDA and large-scale ML systems.

Qualifications

• PhD with 4+ years, MS with 6+ years, or BS with 8+ years of relevant experience in Computer Science, Computer Engineering, or related field.
• Production experience in autonomous driving systems
• Worked on AI foundation models or large-scale ML systems
• Experience driving end-to-end driving models

Responsibilities

• Compose and build the architecture behind next-generation self-driving vehicle technology.
• Work on Prediction, Decision, Planning and Control architecture
• Have exposure to Classical safety stack
• Build robust system-level safety and fallback strategies
• Work on End-to-end data-driven AV pipelines
• Hands on experience in DVLA / VA driving models
• Develop a World Model-based planning and reasoning model
• Engage with Large-scale model inference architecture
• Contribute to integration of innovative research in robotics into our self-driving vehicle technologies.
• Deep knowledge of E2E AV software integration from perception through control, including dependencies, interface management, and performance tuning.

Skills

Autonomous driving

AI/ML systems

System architecture

Robotics experience

Large-scale ML systems

Education

PhD (or equivalent)

MS (or equivalent)

BS (or equivalent)

Tools

CUDA

Job description

NVIDIA is developing the next generation of AI-native autonomous driving systems in the United States. You will contribute to end-to-end autonomous driving architectures spanning perception through control and model inference, with emphasis on safety, scalability, and integration of research into production.

You will collaborate across research and engineering teams, shaping system architecture from 0 to scale while applying knowledge of CUDA and large-scale ML systems.