Manager, Solutions Architecture - Financial Services Capital Markets

What You’ll Be Doing

• Recruit and Mentor architects personally and professionally, aligning with Industry and Company goals.
• Work across teams to drive Financial Services Industry strategy.
• Provide technical leadership on all NVIDIA products pertinent to the industry, directly supporting Industry Business Development and Sales to achieve design wins and execute industry strategy.

What We Need To See

• Hold an M.Sc. or Ph.D. in computer science, data science, electrical engineering, or computer engineering from a leading university (or equivalent experience).
• 4+ years of proven strong technical leadership in team development, managing KO's, communication excellence, problem-solving, sharing direction with critical thinking, and fostering team collaboration.
• 8+ overall years of experience in one or more diverse areas such as systems architecture (Clusters, Kubernetes, Slurm, Spark, Storage, Networking, DGX platform, DGX Cloud, AWS, GCP, ODI, Azure), development (C/C++, Python, Jupyter Labs), model training (Pytorch, Jax, Tensorflow, XGBoost, Transformers, GenAI, back-testing), or Graph Neural Networks.
• Experience or working insights in NVIDIA software pipelines (data curation, training, validation, production) and GPU products and software such as NeMO Foundation, HPC-SDK, Triton, NVIDIA AI Enterprise, NVIDIA GPU Cloud).
• Excellent presentation skills with the ability to explain sophisticated ideas.
• Experience in cross-collaboration, driving technical excellence, and growing leaders within the team, executive alignment, and vision to think out the box solutions.
• Good to have experience working with the Financial Services industry, either within or supporting industry customers/partners.

Ways To Stand Out In The Crowd

• People Management and leadership experience
• GPU Development in HPC and/or AI applied to Finance use cases
• In-depth software development life cycle, data science or data engineering expertise
• Stellar communication skills
• Familiarity in statistical analysis in Finance (Binomial Trees, Linear/Non-Linear, Linear Regression), model or algorithm development (back-testing, GenAI, Transformers)