Senior Software Engineer - Autonomous Vehicles

Details

NVIDIA is developing full-stack platforms for autonomous machines, including self-driving cars and intelligent robots. The role focuses on runtime intelligence and safety architecture for next-generation autonomous driving systems, bridging large-scale learned driving models with deterministic planning and vehicle-level safety guardrails.

Responsibilities

• Design and integrate planning frameworks combining end-to-end learned driving models with classical trajectory planning and deterministic safety systems.
• Develop runtime arbitration and safety enforcement mechanisms between AI-generated trajectories and rule-based safety constraints.
• Build scalable architectures that enable large AI driving models to operate within automotive compute, latency, and real-time execution constraints.
• Develop execution frameworks ensuring AI-generated behaviors satisfy vehicle dynamics, collision avoidance, passenger comfort, and safety requirements in real time.
• Implement safety-oriented planning capabilities, including trajectory validation, fallback handling, runtime policy gating, and Minimum Risk Maneuver strategies.
• Partner with AI, planning, controls, and systems teams to productize learned driving models for deployment in autonomous vehicle systems.
• Analyze and debug autonomy edge cases involving uncertainty, model failure modes, planner disagreement, and real-world safety constraints.
• Improve observability, reliability, and debuggability across autonomy planning systems operating in simulation and on-vehicle environments.
• Drive architectural decisions balancing AI capability, system robustness, safety, and embedded deployment efficiency.
• Influence next-generation autonomy architecture, defining how foundation-model and learning-based driving systems coexist with production-grade safety-critical vehicle platforms.

Requirements

• BS, MS, or PhD, or equivalent experience, in Computer Science, Robotics, Electrical Engineering, AI/ML, or a related technical field.
• 12+ years of relevant industry experience in autonomous systems, robotics, AI infrastructure, or safety-critical software systems.
• Strong software engineering fundamentals and production C++ development experience.
• Strong understanding of autonomous vehicle planning, trajectory generation, motion planning, or robotics systems.
• Experience with machine learning systems and understanding of learned-model behavior under uncertainty and real-world edge cases.
• Experience delivering scalable, production-quality systems from architecture through deployment.
• Strong debugging, systems integration, and performance optimization skills for real-time systems.
• Excellent communication and cross-functional technical leadership abilities.

Preferred Qualifications

• Experience deploying machine learning models into real-time embedded or robotics systems.
• Deep understanding of classical planning systems and end-to-end learning approaches for autonomous driving.
• Experience with runtime safety validation, fallback systems, policy gating, or safety arbitration frameworks.
• Familiarity with foundation-model-based driving systems, learned planners, generative trajectory models, or AI-native autonomy stacks.
• Experience with large-scale autonomy simulation, scenario replay, evaluation infrastructure, or safety validation pipelines.
• Strong intuition for bridging offline AI model capability and production deployment constraints.
• Passion for solving challenging engineering problems at the intersection of AI, robotics, and real-world deployment.

Compensation and Benefits

The base salary range is USD 224,000–356,500, determined by location, experience, and the compensation of employees in similar positions. The role also includes eligibility for equity and benefits.

NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.