Remote GenAI Solutions Architect (Data Science)

NVIDIA; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Remote work flexibility

Job summary

NVIDIA is seeking a Solutions Architect (Data Science) to drive deep technical engagement with Enterprise customers and partners. You will connect customer workloads to NVIDIA’s platform, acting as a trusted advisor and enabling developers and enterprises to adopt and scale our AI hardware and software ecosystem.

The role requires strong technical depth in generative AI, LLMs, and scalable software engineering, with a focus on presales, partnerships, and enablement across APAC and HQ teams.

Qualifications

• Professional, long-term experience in AI/ML/DL
• Strong customer-facing or presales/consulting experience
• Experience with AI/ML/Big Data frameworks
• Proven ability to lead technical engagements with enterprise customers
• Familiarity with LangChain and LangGraph for LLM orchestration
• Experience with Kubernetes and data center hardware/storage/networking

Responsibilities

• Drive technical engagements with Enterprise customers and partners
• Co-design scalable architectures and define deployment milestones
• Lead PoC demos and write Python data pipelines for AI/DL models
• Collaborate with cross-functional teams to build GenAI full stack solutions
• Document knowledge through whitepapers, blogs, and wiki articles
• Partner with regional HQ teams to plan best-fit solutions for Partners
• Run NVIDIA Deep Learning Institute and skills transfer sessions

Skills

AI/ML/DL

Customer-facing

Presales

LangChain

LangGraph

Kubernetes

Data Science

PoC

Python

Distributed Systems

Education

BS/MS/PhD in CS/Engineering

Tools

NVIDIA Nemo

NIM

NVIDIA SDK

MLOps tools

Job description

NVIDIA is seeking a Solutions Architect (Data Science) to drive deep technical engagement with Enterprise customers and partners. You will connect customer workloads to NVIDIA’s platform, acting as a trusted advisor and enabling developers and enterprises to adopt and scale our AI hardware and software ecosystem.

The role requires strong technical depth in generative AI, LLMs, and scalable software engineering, with a focus on presales, partnerships, and enablement across APAC and HQ teams.