Solutions Architect at NVIDIA

Sydney, New South Wales, Australia

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

Professional, long-term experience as a Data Scientist (focus on AI/DL/ML) developing/supporting customer-facing projects in computer vision, Conversational AI, or data analytics technologies, especially in RAG and Agentic AI workflows
BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience)
Strong customer-facing or presales/consulting and technical experience and skills with AI/ML/Big Data frameworks
5+ overall years of work-related experience in deep learning, data science or software development with knowledge of parallel computing with GPUs
Good planning and long-term strategic engagement and orchestration with a broad ecosystem of stakeholders from customer, to internal and external parties
Clear written and oral communication skills with the ability to collaborate with management and engineering; share knowledge with clients, partners and co-workers
Self-starter (inferred from "You are a self-s")

Responsibilities

Become an NVIDIA AI expert and enable GSI developers to adopt NVIDIA Nemo and NIMs for their Generative AI offerings, platforms and client services
Construct complex workflows with multiple steps for AI agents to analyze, strategize, perform tasks, access APIs, and fix errors autonomously
Work with Business Managers to craft the vision, actionable and effective strategies for the broader GSI group and 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
Encourage industry executives and GSI leaders by articulating the business value from the state-of-the-art in Generative AI
Create or run Proof of Concept and Demos that require presentation skills, explanation of complex topics, writing Python code to execute data pipelines, train ML/DL models, and deploy on container-based orchestrators
Answer questions and provide mentorship to the GSI Ecosystem; work with Partner Business Managers to assist partners and customers on mission-critical projects; help build GPU-enabled Accelerated Compute datacenters and maximize investment
Partner with APAC Regional and HQ Engineering, Product and Sales teams to develop and plan best suitable solutions for Partners; enable development and growth of product features through customer feedback and proof-of-concept evaluations
Run NVIDIA Deep Learning Institute and Skills Transfer sessions with GSIs, Customers, OEMs and partners around NVIDIA & others HW and SW solutions

Skills

Key technologies and capabilities for this role

Generative AILarge Language ModelsLLMsNVIDIA NemoNIMsAI AgentsDeep LearningScalable Software EngineeringWorkflowsAPIs

Questions & Answers

Common questions about this position

What is the employment type for this Solutions Architect role?

This is a full-time position.

Is this Solutions Architect role remote or office-based?

This information is not specified in the job description.

What key skills are required for the Solutions Architect (Data Science) position?

The role requires deep expertise in generative AI, large language models (LLMs), and scalable software engineering practices, along with Python coding for data pipelines, ML/DL models, and container-based deployment.

What is the team structure like for this role at NVIDIA?

You will work within the ANZ team as part of the Solutions Architecture team, partnering with Global Systems Integrator (GSI) partners, AI consulting firms, Business Managers, other Solutions Architects, engineering, product, and business teams.

What makes a strong candidate for this Solutions Architect role?

Strong candidates will have technical authority in AI and LLMs, experience managing technical partnerships, project orchestration skills, and the ability to present complex topics and mentor partners.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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