Solutions Architect, Retail Data Science

$148,000 - $276,000/Yr

Nvidia - Santa Clara, CA

Full-time - Senior

Remote - Santa Clara, CA

Computer and Electronic Product Manufacturing

About the position

The Senior Solution Architect at NVIDIA will focus on developing innovative Generative AI solutions for top Retail, CPG, and QSR companies. This role involves working closely with Fortune 100 customers to drive technology adoption and secure design wins in Data Center, Edge, and Cloud Deployments. The architect will leverage NVIDIA's Generative AI platforms to create solutions for various use cases in the Retail Industry, including forecasting and supply chain optimization.

Responsibilities

• Drive NVIDIA technology adoption and secure innovative design wins in Data Center, Edge, and Cloud Deployments.
• Develop and demonstrate solutions based on NVIDIA's Generative AI platforms (NeMo, NIM).
• Build innovative blueprints for key Retail Industry use-cases such as forecasting, supply chain optimization, recommendation, and cybersecurity.
• Collaborate with NVIDIA Engineering, Product, and Sales teams to secure design wins and enhance product features through customer feedback.

Requirements

• BS in Engineering, Mathematics, Physics, or Computer Science or equivalent experience.
• 5+ years experience as a Data Scientist, Data Engineer, or Software Engineer with a proven track record in developing LLM workflows and writing code in Python.
• Ability to communicate ideas and code clearly through GitHub, documentation, and presentations.
• Enjoy collaborating with teams across the organization such as Engineering/Research, Sales, Product, and Marketing.
• Effective verbal/written communication and technical presentation skills.
• Self-starter with a passion for growth and enthusiasm for continuous learning.

Nice-to-haves

• External customer facing skill-set and background.
• Development experience with NVIDIA software platforms, libraries, and GPUs.
• Experience working with Commercial and Open Source GenAI solutions.
• Experience building RAG workflows and fine-tuning LLM models.
• Knowledge of MLOps technologies such as Docker/containers, Kubernetes, and data center deployments.

Benefits

• Highly competitive salaries
• Comprehensive benefits package
• Equity options
• Excellent engineering work culture