Deep Learning Engineer, End-To-End Autonomous Driving

Details

At NVIDIA, we are seeking exceptional engineers to join our autonomous driving team to design, implement, and deploy cutting-edge end-to-end autonomous driving systems, running on NVIDIA chips in mass-production vehicles. Our strategy has evolved from AI 1.0 — building a driver from scratch — to AI 2.0 — teaching an intelligent agent to drive. This next phase leverages LLMs, VLMs, and VLAs to bring outstanding reasoning, planning capabilities, and interactivity with the driving system to autonomous vehicles and general 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, and 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 (e.g., PyTorch, TensorFlow).
• Familiarity with C++ for model deployment and integration in safety-critical systems.
• Master’s degree or PhD (or equivalent experience).
• 6+ years of work experience in autonomous vehicles (AV) or a related field.

Ways to Stand Out

• 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.

Compensation & Other Info

• Base salary ranges by level: Level 4 — 184,000 USD to 287,500 USD; Level 5 — 224,000 USD to 356,500 USD. Final base salary will be determined based on location, experience, and pay of employees in similar positions.
• You will also be eligible for equity and benefits.
• Applications for this job will be accepted at least until August 17, 2025.

Equal Employment

NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. The company does not discriminate on the basis of protected characteristics.

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