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NVIDIA
NVIDIA
H1B Visa SponsorArtificial IntelligenceHealthcareManufacturing
NVIDIA develops accelerated computing and artificial intelligence technologies used across gaming, data centers, cloud computing, healthcare, manufacturing, automotive, and robotics. Its work spans graphics processing units, AI platforms, simulation, and industry-focused solutions, including NVIDIA Omniverse for collaborative 3D workflows, NVIDIA DRIVE for autonomous vehicle development, and NVIDIA Clara for healthcare applications. The company brings together large technical teams working on the infrastructure and software that support advanced computing, simulation, and AI-driven analytics.
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NVIDIA Solutions Architect, Data Science (Remote Australia)

Lead NVIDIA’s customer and partner adoption of generative AI platforms across Australia. Design scalable architectures, proofs of concept, and Agentic AI solutions with NVIDIA hardware and software.

AUAustraliaRemoteFull-timeMiddleSeniorEnglish RequiredSolutions Engineer
CloudKubernetesMicroservicesPython

Description

  • Lead technical engagements with enterprise customers and partners across multiple industries
  • Map customer workloads to NVIDIA’s hardware and software ecosystem
  • Advise customers on adopting and scaling NVIDIA platforms
  • Manage technical partnerships and partner enablement with a presales focus
  • Help customers redesign enterprise processes with Agentic AI on NVIDIA platforms
  • Deliver technical engagement, enablement, proof-of-concept demonstrations, and executive relationship support
  • Collaborate with developers, researchers, data scientists, IT managers, and senior leaders
  • Enable adoption of NVIDIA NeMo and NIM across generative AI products, platforms, and client services
  • Co-design scalable architectures, technical direction, integration milestones, and deployment plans with customers and partners
  • Work with Solutions Architecture, engineering, product, and business teams to deliver full-stack generative AI solutions
  • Lead technical engagements, resolve complex issues, and represent customer technical requirements
  • Develop and demonstrate proofs of concept involving Python data pipelines, AI and deep-learning model training, and containerized deployment
  • Create partner and Solutions Architect training, plus whitepapers, blog posts, and wiki content
  • Collaborate with APAC regional and headquarters engineering, product, and sales teams on solution development
  • Deliver NVIDIA Deep Learning Institute and Skills Transfer sessions for customers, OEMs, and partners

Requirements

  • Several years of professional experience as a data scientist working on AI, deep learning, or machine learning projects for customers
  • Background in computer vision, conversational AI, or data analytics technologies
  • Bachelor’s, master’s, or doctoral degree in computer science, electrical or computer engineering, physics, mathematics, another engineering discipline, or a related field, or equivalent experience
  • Strong customer-facing, presales, consulting, and technical experience with AI, machine learning, or big data frameworks
  • At least five years of professional experience in deep learning, data science, or software development
  • Understanding of GPU-based parallel computing
  • Hands-on experience developing retrieval-augmented generation and Agentic AI workflows
  • Experience using LangChain and LangGraph to orchestrate large language models
  • Working knowledge of Kubernetes and data-center compute, storage, and networking
  • Strong written and verbal communication skills
  • Ability to collaborate with management and engineering teams while sharing knowledge with customers, partners, and colleagues
  • Ability to work remotely, organize priorities, and plan effectively within a small team
  • Experience leading technical teams for partners or customers, or advising and consulting on AI projects, is advantageous
  • Experience managing AI or data science projects and coordinating stakeholders is advantageous
  • Experience with the NVIDIA SDK platform, NeMo, NIM, machine learning and deep learning frameworks, and MLOps tools is advantageous
  • Experience designing cloud solutions and working with APIs, microservices, orchestration platforms, storage systems, and data migration techniques is advantageous

Benefits

  • Equal opportunity employment within a diverse workplace
  • Professional development and ongoing learning opportunities
  • Teamwide knowledge-sharing opportunities
  • Remote work arrangement

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