Nvidia VLA Deep Learning Engineer End-To-End Autonomous Driving 

Israel, North District 

299188609

What you will be doing:

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

• Explore novel data generation and collection strategies to improve diversity and quality of training datasets. Develop, pre-train, and optimize LLM/VLM/VLA models for autonomous driving and robotics applications.

• Collaborate cross-functionally to deploy and integrate AI models into vehicle firmware.

• Deliver production-quality, safety-critical software that meets performance, safety, and reliability standards.

What we need to see:

• PhD or Master's degree with equivalent experience.

• 8+ years of experience

• Hands-on experience training LLMs/VLMs/VLAs from scratch, or a proven record as a top-tier ML engineer/researcher passionate about autonomous systems.

• Strong programming skills in Python and proficiency with major deep learning frameworks. Basic familiarity with C++ for model deployment and integration in safety-critical systems.

• Comprehensive grasp of current deep learning structures and improvement methods. Consistent track record of deploying production-grade ML models for self-driving, robotics, or related fields at scale.

Ways to stand out from the crowd:

• Experience developing and shipping LLM/VLM/VLA solutions for autonomous vehicles or general robotics products.

• Publications, contributions to open-source projects, or victories in competitions connected to LLM/VLM/VLA systems.

• Profound comprehension of behavior and motion planning in real-world autonomous vehicle (AV) applications.

• Experience building and training large-scale datasets and models and/or training agents with reinforcement learning.