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Solutions Architect - Financial Service

NVIDIANVIDIA·Semiconductors

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About the role

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:

  • AIGC/LLM/NLP in financial field experience

  • CUDA optimization experience.

  • Experience with Deep Learning frameworks and tools.

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

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

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Aplyr's read

NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.

Synthesized from recent postings & public sources

What's promising

  • NVIDIA leads the GPU market, crucial for gaming and AI applications.
  • The company invests heavily in AI and deep learning, driving technological advancements.
  • NVIDIA's strong market position offers stability and growth opportunities for employees.

What to watch

  • High competition in the semiconductor industry can impact market share.
  • Rapid technological changes require constant adaptation and learning.
  • Intense workload and high expectations may affect work-life balance.

Why NVIDIA

  • NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
  • The company's AI research is at the forefront of deep learning innovation.
  • NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.

Aplyr’s read is generated by AI from public sources. Was it useful?

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About NVIDIA

NVDA$212.45+3.54%

NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.

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