
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.
October 15

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.
• Develop and present engaging training sessions dedicated to NVIDIA’s artificial intelligence and machine learning operations, highlighting software, support, and operational protocols. • Create innovative training materials—including lab exercises, presentations and content aligned with evolving NVIDIA software and support offerings. • Collaborate with product and domain experts to shape new support modules and joint training plans for enterprise customers and authorized learning partners (ALPs). • Provide real-time fixing, learner engagement, and technical mentorship during workshops. • Work closely with lab manager and course developers to optimize training environments for software-specific labs.
• Bachelor’s degree in computer science, engineering, or related domain, or equivalent experience. • Minimum 6 years of professional experience, with at least 2 years focused on AI software or/and MLOps platforms. • Technical proficiency in: Linux, containerization (Kubernetes, Docker), orchestration tools, cloud environments • Hands-on experience with AI Tools, GPU Operator, ML frameworks (CUDA, RAPIDS, PyTorch, TensorFlow), and NVIDIA software stack. • Proven ability to communicate complex concepts to diverse audiences. • Strong English written and verbal communication skills.
• Professional development opportunities
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