1 day ago
Base Salary
$184k - $357k/yr
Responsibilities
- Design and train large-scale generative, imitation, and reinforcement learning models for driving-system planning and reasoning.
- Build, pre-train, and fine-tune LLM, VLM, and VLA systems for autonomous driving and robotics applications.
- Develop data-generation and collection strategies to improve training-data diversity and quality.
- Collaborate with cross-functional teams to deploy AI models in production while meeting performance, safety, and reliability standards.
- Integrate machine learning models with vehicle firmware for 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 experience deploying production-grade machine learning models for self-driving, robotics, or related fields at scale.
- Strong Python programming skills and proficiency with major deep learning frameworks.
- Familiarity with C++ for model deployment and integration in safety-critical systems.
- PhD with 4+ years, or MS or equivalent experience with 6+ years, in Computer Science, Computer Engineering, or a related technical field.
- Preferred qualifications include LLM/VLM/VLA deployment in autonomous vehicles or robotics, relevant publications or open-source contributions, behavior and motion-planning expertise, large-scale dataset and model development, and real-time algorithm optimization.
Benefits
- Base salary is provided according to location, experience, and comparable employee pay, with equity and benefits also available.
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.