Hybrid Senior Deep Learning Engineer – End-To-End Autonomous Driving

at NVIDIA

• Job title: Senior Deep Learning Engineer – End-To-End Autonomous Driving
• Job type: Full Time
• Experience level: Senior
• Salary: $184,000 - $356,500 per year
• Degree requirement: Postgraduate Degree
• Tech skills: Python
• Location requirements: Hybrid, Santa Clara, United States

About the role

• Engineer designing, implementing, and deploying end-to-end autonomous driving systems at NVIDIA. Collaborating with cross-functional teams to enhance driving capabilities with innovative large-scale models and AI.

Responsibilities

• Design and train innovative large-scale models—including generative, imitation, and reinforcement learning—to improve the planning and reasoning capabilities of our 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.

Requirements

• Hands-on experience building LLMs, VLMs, or VLAs from scratch or a proven track record as a top-tier coder passionate about 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.
• Master's degree or PhD (or equivalent experience).
• 8+ years of work experience in AV or related field.

Benefits

• equity
• benefits