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Solutions Architect - Financial Services

NVIDIA

Beijing, Beijing, ChinaFull-timePosted 1w agoStill listed 1w ago

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At a glance

Compensation
No compensation found
Location
Beijing, Beijing, China
Schedule
Full-time
Work Authorization
Not specified

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Requirements

Credentials this posting asks for.

Master's degree

Job overview

NVIDIA seeks a Solutions Architect for financial services to design AI computing platforms, analyze customer workloads, and co‑develop accelerated solutions. The role collaborates with sales, developers, and product teams, delivering demos, technical projects, and thought leadership on deep learning, data analytics, and HPC for finance.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningData AnalyticsHPCC/C++PythonCUDACUDA-XCloud ArchitecturesParallel ProgrammingQuant AlgorithmsPortfolio OptimizationTrading AlgorithmsLLM TrainingAgent AIDeep LearningHigh Performance Data Analytics

Qualifications

3+ Years Machine Learning/HPC ExperienceOutstanding Verbal and Written Communication SkillsAbility to Work Independently With Minimal DirectionKnowledge of Industry Application Hotspots and Trends in AI for Financial FieldMS or PhD in Engineering, Mathematics, Physics, Computer Science, Data Science, Neuroscience, Experimental Psychology or Equivalent ExperienceFamiliarity With Financial Technology Stacks and Common Quant Workflow Optimization MethodsExperience Using Scale‑Out Cloud and/or HPC Architectures for Parallel Programming

Full job description

NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers. You will work closely with industry sales, developer relationship managers and product teams in the hiring position.

What You’ll Be Doing:

  • Conduct in-depth analysis of customers' latest needs and co-develop accelerated computing solutions with key customers.

  • Assist in supporting industry accounts and driving research/influencing/new business in those accounts.

  • Deliver technical projects, demos and client support tasks as directed by the Solution Architecture leadership team.

  • Understand and analyze financial customers' workloads and demands for accelerated computing, including but not limited to: quant algorithms, portfolio optimization solving, trading algorithms, LLM training/inference acceleration and optimization, application optimization for Agent AI/RAG, kernel analysis, etc.

  • Assist Top financial customers in onboarding NVIDIA's software and hardware products and solutions, including but not limited to: CUDA, CUDA-X, and our libraries etc.

  • Be an industry thought leader on integrating NVIDIA technology into applications built on Deep Learning, High Performance Data Analytics, Agentic AI and other key applications.

  • Be an internal champion for Data Analytics, Machine Learning, and Deep Learning among the NVIDIA technical community.

What We Need To See:

  • 3+ years’ experience with research/development/application of Machine Learning, data analytics, or HPC work flows.

  • Outstanding verbal and written communication skills

  • Ability to work independently with minimal day-to-day direction

  • Knowledge of industry application hotspots and trends in AI and large models for financial field.

  • Familiarity with financial technology stacks and common quant workflow optimization methods. C/C++/Python programming experience

  • Desire to be involved in multiple diverse and innovative projects

  • Experience using scale-out cloud and/or HPC architectures for parallel programming

  • MS or PhD in Engineering, Mathematics, Physics, Computer Science, Data Science, Neuroscience, Experimental Psychology or equivalent experience.

Ways To Stand Out From The Crowd:

  • Be familiar with algorithm trading pipeline, including data processing, prediction, portfolio optimization, and execution.

  • LLM/Agent/Harness experience in financial field experience

  • Engineering experience in areas such as model acceleration and kernel optimization.

  • Extensive experience in designing and deploying large scale HPC and enterprise computing systems.

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