Solutions Architect (Data Science)

NVIDIA seeks a Solutions Architect (Data Science) for its ANZ team to help Global Systems Integrator (GSI) partners and AI consulting firms build enterprise generative AI offerings on the NVIDIA platform. The role combines technical solution design with partner enablement, project coordination and communication with business and technical stakeholders. Listed locations are Sydney and remote within Australia.

Responsibilities

• Enable GSI developers to adopt NVIDIA NeMo and NIM for generative AI platforms and client services. Design multistep AI-agent workflows that can access APIs, perform tasks and address errors.
• Work with business managers, solutions architects, engineering, product and sales teams to develop full-stack generative AI solutions for enterprise and industry use cases. Explain their business value to executives and GSI leaders.
• Build and present proofs of concept and demonstrations, including Python data pipelines, ML/DL model training and deployment on container-based orchestrators. Mentor partners, support customer projects involving GPU-accelerated datacenters, and use customer feedback and evaluations to inform product development.
• Deliver NVIDIA Deep Learning Institute and skills-transfer sessions for GSIs, customers, OEMs and other partners.

Requirements

• 5+ overall years of work-related experience in deep learning, data science or software development, with knowledge of GPU parallel computing. Customer-facing data science experience involving AI/ML/DL projects, including computer vision, conversational AI or data analytics, particularly RAG and agentic AI workflows.
• BS, MS or PhD in computer science, electrical/computer engineering, physics, mathematics, another engineering field or a related discipline, or equivalent experience. Customer-facing, presales or consulting experience with AI/ML and big-data frameworks; planning, stakeholder coordination, presentation and written and verbal communication skills. Ability to collaborate effectively while working remotely.

Preferred

• Experience leading technical teams or advising partners and customers on AI; managing AI or data science projects; developing with NVIDIA NeMo, NIM, ML/DL frameworks and MLOps tools; or designing cloud solutions involving APIs, microservices, orchestration, storage and data migration.