[Remote] Principal Deep Learning Senior Engineer, End-To-End Autonomous Driving

Note: The job is a remote job and is open to candidates in USA. NVIDIA is seeking exceptional engineers to join their autonomous driving team to design, implement, and deploy cutting-edge end-to-end autonomous driving systems. The role involves building and optimizing large-scale models and collaborating with cross-functional teams to ensure performance and safety standards in production environments.

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

Skills

• 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 equivalent experience) with 13+ years of work experience in AV or related field or PhD with 11 years of work experience in AV or related field
• Experience with LLM/VLM/VLA systems deployable to autonomous vehicles or general robotics
• Publications, open-source contributions, or competition wins related to LLM/VLM/VLA systems
• Deep understanding of behavior and motion planning in real-world AV applications
• Experience building and training large-scale datasets and models
• Proven ability to optimize algorithms for real-time performance in resource-constrained environments and strong track record of taking projects from concept to production deployment

Benefits

• Equity
• Benefits

Company Overview

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