Nvidia Senior AI Technical Instructor 

United States, California 

530484021

What you’ll be doing:

• Training Delivery: Conduct face-to-face and remote training sessions for NVIDIA’s customers and partners, with a willingness to travel up to 50% as required.

• Content Development:Help d

• Collaboration: Collaborate with internal and external subject matter experts (SMEs) to draft course proposals aligned with market trends and customers' requirements.

• Train the Trainers: Recruit and train internal team members to deliver specific sessions of workshops.

• Lab-Based Training: Create engaging lab-based training, incorporating diagrams, explanatory videos, and interactive hands-on exercises.

• Feature Integration: Collaborate with SMEs to integrate key features of NVIDIA solutions into project-based learning experiences.

• Instructor Support: Develop instructor delivery notes, certification criteria, and assessment materials.

• Quality Assurance: Participate in internal test deliveries to ensure high-quality learning experiences. Actively seek feedback from students, and industry partners to enhance course content.

What we need to see:

• Proficiency in delivering training and presentations, with the ability to effectively communicate technical concepts to partner audiences.

• Demonstrated ability to design and implement accelerated computing solutions. Familiarity with tools such as SLURM, Kubernetes, Docker containers, Git, Python, CUDA, RAPIDS, and cloud service providers (AWS, Azure, GCP) is important.

• A bachelor's degree in computer science, mathematics, engineering, or equivalent experience.

• 8+ years of technical field or training experience, with at least 5+ years in data center-related technologies supporting AI such as storage, networking, or accelerated computing. Training delivery experience is required.

• Strong communication, interpersonal, and writing skills in English.

• Ability to work multi-functionally across different levels of a matrixed organization.

Ways to stand out from the crowd:

• Experience in delivering and developing in-depth training for technical selling audiences.

• Proven experience in Field Engineering or Solutions Architect roles.

• Experience in optimizing workloads with GPU, like CUDA, CuDNN and TensorRT.

• A master's degree in computer science, mathematics, engineering, or an equivalent level of expertise and experience.

• Expertise in AI data center workloads and technologies.