Solutions Architect, AI and ML

• Work 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 proofs of concept addressing customers’ critical business needs with NVIDIA hardware and software
• Partner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions
• Prepare and deliver technical content to customers, including presentations and workshops
• Conduct regular technical customer meetings covering project and product roadmaps, feature discussions, and new technologies
• Establish close technical ties with customers to facilitate rapid resolution of customer issues
• Engage directly with developers, researchers, and data scientists at strategic technology customers
• Work with business and engineering teams on product strategy
• Drive end-to-end technology solutions based on customer business needs

Requirements

• 3+ years of Solutions Engineering or similar Sales Engineering experience, or equivalent experience
• 3+ years of work-related experience in Deep Learning and Machine Learning
• Experience with TensorFlow or PyTorch, GPU, and CUDA
• BS, MS, or PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or another Engineering field, or equivalent experience
• 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, and data center deployments
• Ability to use at least one scripting language, such as Python
• Good programming and debugging skills
• Ability to communicate ideas and code clearly through documents and presentations
• AWS, GCP, or Azure Professional Solution Architect Certification is a differentiator
• Hands-on experience with NVIDIA GPUs and SDKs such as CUDA, RAPIDS, or Triton is a differentiator
• System-level experience with GPU-based systems is a differentiator
• Experience with Deep Learning at scale is a differentiator
• Familiarity with parallel programming and distributed computing platforms is a differentiator

Core Competencies

Demonstrates expertise in building and deploying AI/ML solutions using NVIDIA technologies on cloud platforms, with a strong foundation in Deep Learning and Machine Learning. Capable of engaging with technical stakeholders to drive business solutions and deliver impactful presentations.

Highest-signal resume keywords

• Solutions Engineering Experience
• Deep Learning and Machine Learning
• TensorFlow or PyTorch
• Cloud Computing Environments
• NVIDIA GPUs and SDKs

ATS Optimization Keywords

Hard Skills

• Deep Learning
• Machine Learning
• TensorFlow
• PyTorch
• CUDA
• Scripting Language (Python)
• Programming and Debugging Skills
• Cloud Computing (AWS, GCP, Azure)
• DevOps/ML Ops Technologies
• Parallel Programming

Soft Skills

• Communication Skills
• Technical Presentation Skills

Certifications & Qualifications

• AWS Professional Solution Architect Certification
• GCP Professional Solution Architect Certification
• Azure Professional Solution Architect Certification

Industry Keywords

• AI Solutions
• ML Solutions
• Cloud Service Providers
• Technical Customer Engagement
• Business Strategy

Tools & Technologies

• NVIDIA Hardware and Software
• Docker/Containers
• Kubernetes
• Data Center Deployments