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Solutions Architect - Data Science

NVIDIA· Architect, Solutions
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Hybrid (Remote / Australia)full-timePosted 2w ago

About the role

Solutions Architect (Data Science) to drive technical engagement with Enterprise customers and partners, bridging customer workloads to NVIDIA’s platform with a strong presales focus and deep expertise in generative AI, LLMs, and scalable software engineering.

Responsibilities

  • Becoming an NVIDIA AI expert and enabling developers to adopt NVIDIA Nemo and NIMs for Generative AI offerings, platforms and client services.
  • Co-design advanced, scalable architectures with Enterprise customers and Partners, defining technical direction, integration milestones, and deployment plans.
  • Closely partner with other Solutions Architects, engineering, product and business teams at NVIDIA to build GenAI full stack solutions for industry vertical and enterprise use cases.
  • Lead technical engagements, helping customers troubleshoot, resolve complex issues, and advocate for their technical needs.
  • Creating or running Proof of Concept and Demos that require presentation skills, explanation of complex topics, writing Python code to execute data pipelines and train AI/DL models and deploy on container-based orchestrators.
  • Document what you know, and guide others (training partners and Solutions Architects, whitepapers/blogs/wiki articles).
  • Partner with APAC Regional and HQ Engineering, Product and Sales teams to develop, plan best suitable solutions for Partners; enable development and growth of product features through customer feedback and PoCs.
  • Run NVIDIA Deep Learning Institute and Skills Transfer sessions with Customers, OEMs and partners around NVIDIA & others HW and SW solutions.

Qualifications

  • Professional, long-term experience as a Data Scientist (AI/DL/ML) with customer-facing project experience in computer vision, Conversational AI, or data analytics technologies.
  • BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, Engineering or related fields (or equivalent experience).
  • Strong customer-facing or presales/consulting and technical experience with AI/ML/Big Data frameworks.
  • 5+ years of work experience in deep learning, data science or software development with knowledge of GPU-based parallel computing.
  • Strong development experience with RAG and workflows for Agentic AI applications.
  • Excellent planning and long-term strategic engagement with a broad ecosystem of stakeholders.
  • Developer experience with LangChain and LangGraph for orchestrating LLMs.
  • Experience with orchestration platforms like Kubernetes and data centers including compute, storage, and networking.
  • Clear written and oral communication skills, ability to collaborate with management and engineering, and share knowledge with clients, partners, and teammates.
  • Self-starter with growth mindset, passion for continuous learning, strong presentation and remote-work capability.

Skills

Required:AI/ML/Big Data frameworks

Benefits

  • Not explicitly listed in the description; included as standard NVIDIA benefits in similar roles may apply
Last updated Oct 9, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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