Level

NVIDIA

Solutions Architect - Data Science

NVIDIA is hiring a Solutions Architect - Data Science for a remote role open to applicants in Australia. Level rates it ; you can apply on Level.

AI in this role

langchainlanggraph
ragml-opscomputer-vision

We’re hiring a Solutions Architect (Data Science) to drive technical engagement with Enterprise customers and partners across a variety of industries. In this role, you’ll connect real-world customer workloads to NVIDIA’s hardware and software ecosystem, helping developers and enterprises adopt and scale our platforms. We’re looking for someone with strong technical depth who can serve as a trusted advisor, bridge complex challenges to innovative solutions, and grow into a strategic resource for the customers and partners you support. This is a role that requires a combination of technical authority as well as good experience in managing technical partnerships and enablement with a strong presales focus. This role will help inspire our customers to reimagine, reinvent and operate enterprise business processes using Agentic AI, leveraging the NVIDIA platform. This is a highly technical role that requires deep expertise in generative AI, large language models (LLMs), Ai Frameworks and scalable software engineering practices, but also requires a focus on successfully managing projects and strong personal and organisational skills orchestrating both internal and external relationships with support from the broader ANZ NVIDIA team.


The NVIDIA Solution Architecture team is the first line of technical engagement and expertise between NVIDIA and our customer ecosystem. Your duties will vary from trusted advisor and enablement to proof-of-concept demonstrations, driving relationships with key executives and managers to evangelize accelerated computing to leverage AI. Dynamically engaging with developers, scientific researchers, data scientists, IT managers and senior leaders is a meaningful part of the Solutions Architect role and will give you experience with a range of partners and concerns. If you’re excited about applied technology and enabling others to succeed with advanced platforms, we’d love to hear from you


What you'll be doing:

  • Becoming an NVIDIA AI expert and enabling developers to adopt NVIDIA Nemo and NIMs for their 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. This can vary from building targeted training for partners and other Solutions Architects to writing whitepapers, blogs, and wiki articles, to work through challenging problems with a partner on a whiteboard.
  • 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 proof-of-concept evaluations
  • Running NVIDIA Deep Learning Institute and Skills Transfer sessions with Customers, OEM’s and partners around NVIDIA & others HW and SW solutions.

 

What we need to see:

  • Professional, long-term experience as a Data Scientist (focus on AI/DL/ML) developing/supporting customer facing projects experience on computer vision, Conversional AI, or data analytics technologies.
  • 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 assisting them with.
  • 5+ overall years of work-related experience in deep learning, data science or software development with knowledge of parallel computing with GPUs
  • Strong development experience with RAG and workflows building Agentic AI applications.
  • Good planning and long-term strategic engagement and orchestration with a broad ecosystem of stakeholders from customer, to internal and external parties.
  • Developer experience with LangChain and LangGraph orchestrating LLMs.
  • Working experience of Orchestration platforms like Kubernetes and datacentre including compute, storage, and networking.
  • Clear written and oral communication skills with the ability to collaborate with management and engineering. Share knowledge with clients, partners and co-workers.
  • You are a self-starter with attitude for growth, passion for continuous learning and sharing findings across the team, with excellent presentation, verbal and written communication skills and you are able to work remotely, planning well with strong partnering with a small team with an attitude for growth, passion for continuous learning and sharing findings across the team

 

Ways to stand out from the crowd:

  • Have experience leading technical teams working with partners and or customers, or consulting/advisor experience in the AI space.
  • AI/Data Science project management, liaising with multiple stakeholders to drive projects, and coordinating resources inside (and outside if relevant) the organization.
  • Proficient developer experience on NVIDIA SDK platform using Nemo and NIM, ML/DL frameworks and MLOps ecosystem of tools and solutions in the cloud and on-prem.
  • Experience with cloud based solution designing, APIs and Microservices, orchestration platforms, storage solutions and data migration techniques
  • Have a willingness and ability to dig into unfamiliar territories to tackle sophisticated problems and be a phenomenal listener.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you!


NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

How we rate this

Solutions Architect - Data Science at NVIDIA rates 73 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGML OpsComputer visionLangChainLangGraph

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you monitor a model once it's live, and how do you know it needs retraining?
  3. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  4. What's a project where you used LangChain hands-on?
  5. Walk me through how you've used LangGraph in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: RAG, ML Ops, Computer vision, LangChain, and LangGraph. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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