Deep Learning Senior Engineer, End-To-End Autonomous Driving

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

Job summary

NVIDIA is seeking exceptional engineers to join our autonomous driving team to design, implement, and deploy end-to-end autonomous driving systems on NVIDIA chips in mass-production vehicles.

We aim to advance AI in driving with LLMs, VLMs, and VLAs, delivering safe, reliable systems. Eligible candidates include PhD or MS with extensive ML/CS experience and strong Python/C++ skills.

Qualifications

• Hands-on experience building LLMs, VLMs, or VLAs from scratch or 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.
• PhD with 4+ years, MS (or equivalent experience) with 6+ years of related technical experience.

Responsibilities

• Design and train large-scale models—including generative, imitation, and reinforcement learning—for autonomous driving systems.
• Build, pre-train, and fine-tune LLM/VLM/VLA systems for deployment in real-world robotics applications.
• Explore data generation strategies to improve training data diversity and quality.
• Collaborate with cross-functional teams to deploy AI models in production environments with safety and reliability standards.
• Integrate ML models with vehicle firmware for production-quality software.

Skills

LLMs / VLMs / VLAs

DL architectures

Model deployment

Python & DL frameworks

C++ for deployment

Education

PhD with 4+ years

MS with 6+ years

Tools

PyTorch

TensorFlow

Job description

At NVIDIA, we are seeking exceptional engineers to join our autonomous driving teamto design, implement, and deploy cutting‑edge end‑to‑end autonomous driving systems, running on NVIDIA chips in mass‑production vehicles. Our strategy has evolved fromAI 1.0 — building a driver from scratch — to AI 2.0 — teaching an intelligent agent to drive. This next phase leveragesLLMs, VLMs, and VLAsto bring unprecedented reasoning, planning capabilities, andinteractivity with the driving systemto autonomous vehicles and general robotics. Let’s build the future of autonomy—together!

What You’ll Be Doing:

• 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.

What We Need to See:

• Hands‑on experience building LLMs, VLMs, or VLAs from scratchora 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.
• PhD with 4+ years, MS (or equivalent experience) with 6+years of relevant experience in Computer Science,Computer Engineering, or a relatedtechnical field.

Ways to Stand Out from the Crowd:

• 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.

#AutonomousVehicles

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 10, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

#deeplearning