Sales Solutions Engineer

This is a fully remote position, open to applicants in Texas.

📋 Description

• Engage partners to promote the adoption of our AI solutions across diverse industries.

• Assist partners in identifying and constructing a Secure Factory utilizing NVIDIA AI Use Cases for both core and edge applications.

• Collaborate with partners to create and conduct Secure AI Factory workshops.

⛳️ Requirements

• Looking for substantial experience in end-to-end architecture/design across various technology domains for Data Center and hybrid cloud solutions.

• Proficient in public, hybrid, and private cloud computing, along with architecture experience in Virtualization, X86 Architectures, or Operating Systems.

• Experienced in designing and/or deploying Data Center solutions, including traditional DC standalone designs and VXLAN fabric-based architectures.

• Proven ability to provide consumable documentation detailing best practices for deployments related to application acceleration, automation/management efficiencies, enterprise edge, and/or AI/ML solutions.

• A minimum of 6 years of experience in any combination of Datacenter, Storage, Compute, Applications, Big Data, Converged Infrastructure, AI infrastructure, or Data Center Networking.

• Bachelor's Degree or equivalent in Computer Science, Computer Engineering, Electrical Engineering, or a related field.

• An advanced degree is preferred.

• Experience collaborating with partners to develop and execute Go-To-Market activities.

• Knowledge and comprehension of networking protocols and technologies.

• Exceptional presentation skills - capable of delivering engaging workshops to both technical and non-technical audiences on AI-related topics.

• Experience with AI technologies from vendors such as Nvidia, IBM, Microsoft, Dell, NetApp, HPE, and/or other AI providers.

• Comprehensive understanding of language models, including but not limited to GPT-3, BERT, or similar architectures.

• Expertise in training and fine-tuning Large Language Models (LLMs) using popular frameworks like TensorFlow, PyTorch, or Hugging Face Transformers.

• Experience in deploying LLM models in cloud environments (e.g., AWS, Azure, GCP) and on-premises infrastructure.

• Familiarity with containerization technologies (e.g., Docker or equivalent experience) and orchestration tools (e.g., Kubernetes) for scalable and efficient model deployment.

🏝️ Benefits

• Opportunity to work with cutting-edge AI technologies.

• Collaborative work environment with industry-leading partners.

• Professional development and training opportunities.