TavilyRemote · London, United Kingdom; Remote - Europe11h ago
NVIDIAPosted 4w ago
Solutions Architect - Financial Services at NVIDIA scores 70 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
Design and optimize AI and HPC computing platforms for financial services clients, focusing on LLMs, agentic AI, and quantitative workloads.
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.
Prepare for this job
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Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where hpc was part of your work. What did you do?
- Tell me about a project where llm training was part of your work. What did you do?
- Tell me about a project where agentic ai was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Rag, Machine Learning, Hpc, Llm Training, and Agentic AI. 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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