Developer Advocate Engineer

October 10

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NVIDIA

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GPU-accelerated computing • artificial intelligence • deep learning • virtual reality • gaming

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Description

• Stay abreast of the latest developments in HPC & AI technologies and develop proof of concept for real-world scientific and enterprise applications. • Build and refine training materials, and mentor team members at the events. • Collaborate and provide feedback to NVIDIA product teams to help with product adoption, bugs, feature requests, and additional activities through our hackathon program. • Promote through publishing blogs and papers, facilitating presentations, and using other media that convey the impact of the work accomplished by teams at the hackathons. • Mentor developers and researchers to integrate NVIDIA technology using AI & HPC architecture to support scientific and enterprise applications. • Assist in recruiting sites, identifying mentors, and key applications for Open Hackathons and Bootcamps. • Assess each hackathon's computing and software infrastructure. • Write comprehensive internal feedback reports and find opportunities for improvements.

Requirements

• 8+ Years of enterprise and academic experience in the Artificial Intelligence and High Performance Computing domain. • Master's degree in Science or Computer Engineering (or equivalent experience) • Fluent in using NVIDIA accelerated computing stack for HPC and AI workloads • Experience working with DevOps including but not limited to Docker/Containers, Kubernetes, and data center deployments. • Capability to think strategically, while jumping directly into day-to-day event and account management. • Ability to thrive in a highly dynamic environment and to lead change through multi-functional teamwork. • Proven ability to understand partners' goals, and distill that feedback into an action plan that addresses core needs. • Excellent verbal, written communication, and interpersonal skills. • Experience in using Cloud API and Microservices for HPC, ML & DL. • Background in using NVIDIA AI software stack for Enterprise and Data Science Workloads. • Experience in using NVIDIA CUDA architecture for code optimizations. • Experience in facilitating and instructing at group training events.

Benefits

• equity • benefits