NVIDIA is looking to assist customers with adoption of GPU hardware and software, as well as building and deploying Machine Learning (ML) and Deep Learning (DL) solutions on various Cloud Computing Platforms
Requirements
- 3+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU, and CUDA experience
- Established track record of deploying solutions in cloud computing environments including AWS, GCP, or Azure
- Knowledge of DevOps/ML Ops technologies such as Docker/containers, Kubernetes, data center deployments
- Ability to use at least one scripting language (i.e., Python)
- Good programming and debugging skills
- Ability to communicate your ideas/code clearly through documents, presentation etc
- AWS, GCP or Azure Professional Solution Architect Certification
Responsibilities
- Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s ML/DL and data science software and hardware technologies
- Build and deploy AI/ML solutions at scale using NVIDIA's AI software on cloud-based GPU platforms
- Build custom PoCs for solution that address customer’s critical business needs applying NVIDIA hardware and software technology
- Partner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions for ML/DL and other software solutions
- Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc
- Conduct regular technical customer meetings for project/product roadmap, feature discussions, and intro to new technologies
- Establish close technical ties to the customer to facilitate rapid resolution of customer issues
Other
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or other Engineering fields or equivalent experience
- 3+ years of Solutions Engineering (or similar Sales Engineering roles) or equivalent experience
- Occasional travel is required for local on-site visit to customers and industry events
- Ability to communicate effectively with developers, researchers, and data scientists
- Ability to work with business and engineering teams on product strategy
