Principal Deep Learning Engineer – End-To-End Autonomous Driving

🕒 March 20

🏄 California – Remote

🏄 California – Remote

💵 $272k - $431.3k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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 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.

🏖️ Benefits

• equity • benefits