At NVIDIA, we are looking for a Solution Architect, Data Science – Retail to design scalable, data-driven solutions for dynamic retail organizations. In this role, you will help leading Retail and CPG companies implement AI platforms for predictive intelligence and automation across demand planning, logistics optimization, and customer recommendations.

What You'll Do

Drive NVIDIA technology adoption at key Retail & CPG customers and secure design wins in Data Center, Edge and Cloud Deployments.
Become a trusted technical advisor, working on projects to deploy AI solutions in production using Data Processing for Retail.
Lead customer proof-of-concepts (PoCs) for next-gen platforms targeting use-cases like forecasting, logistics, and customer recommendation at scale.
Collaborate with NVIDIA Engineering, Product, and Sales teams on innovative AI optimization techniques to assist in developing solutions and providing customer feedback.
Drive adoption of NVIDIA's Accelerated Compute Platforms by growing customer Software, DevOps and MLOps capabilities using our modern architectures and blueprints.

What We're Looking For

MS or PhD in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent experience).
5+ years of experience in data architecture, data science solutions, or large-scale analytics systems, working with enterprise developers and the research community.
Detailed industry knowledge of Retail Analytics (demand forecasting, supply chain optimization, personalized recommendations).
Experience with ML frameworks or data science stacks (PyTorch, TensorFlow, RAPIDS) and deep understanding of data pipelines, ETL processing, and real-time data streaming with frameworks like Spark, Kafka, Databricks, or Snowflake.
Ability to collaborate across teams such as Engineering/Research, Sales, Product, and Marketing, thinking creatively to debug and solve complex problems.
Excellent communication and presentation skills with the ability to drive technical discussions with both engineers and executives.

Nice to Have

Expertise in supply chain optimization, recommender systems, or behavioral data analytics at large scale.
Strong fundamentals in optimization and decision intelligence (e.g., linear/mixed-integer programming, routing, allocation, or planning algorithms).
Experience with NVIDIA GPUs and software libraries, such as CuOpt, cuVS, RAPIDS, NeMo Retriever, or NVIDIA NeMo Framework.
Prior experience with AI at scale on cloud environments (AWS, Azure, GCP) and on-premises infrastructure.
Experience with containerization, orchestration technologies, monitoring, and observability solutions for AI deployments.

Technical Stack

ML Frameworks: PyTorch, TensorFlow, RAPIDS
Data Platforms: Spark, Kafka, Databricks, Snowflake
NVIDIA Technologies: NVIDIA GPUs, CuOpt, cuVS, NeMo Retriever, NVIDIA NeMo Framework
Cloud Environments: AWS, Azure, GCP