Solutions Architect, Financial Services - Data Center and Infrastructure

## Responsibilities - Financial Services Engagement: Work directly with trading firms and banks to leverage NVIDIA’s advanced technologies for financial workloads. - Infrastructure Design: Implement sustainable data center architectures that optimize energy efficiency and reduce environmental impact. - Technical Specialist: Serve as a technical specialist for GPU and networking products, collaborating closely with account managers to secure design wins. - Collaboration: Work closely with product management, engineering, and sales teams to develop and deliver comprehensive AI and accelerated computing solutions. - Industry Interaction: Dynamically engage with developers, industry researchers, data scientists, and IT managers to solve a range of technical challenges. - RA Reviews: Lead technical project aspects of complex data center deployments, including the review and validation of Reference Architectures (RA) for large-scale financial infrastructure. ## Requirements - BS, MS, or PhD degree in Machine Learning, Computer Science, or a related technical field. - Financial Firm Experience: Proven experience working within Financial Services firms. - Accelerated Computing: Minimum of 8 years of experience in AI and accelerated technologies. - Pre-Sales Expertise: Proven experience driving the technical pre-sales process and engaging with customer engineers and architects. - Large-Scale Systems: Proven experience with large-scale systems management and infrastructure automation. - GPU Stack: Experience with NVIDIA GPUs and related software stacks, such as cuDNN and NCCL. - Core Infrastructure: Strong knowledge of AI and data center technologies, including proficiency in Operating Systems and Linux kernel drivers. - Communication: Solid written and oral communication skills with familiarity in collaborative environments. ## Nice to Have - Cloud Platforms: Proficiency in cloud platforms (AWS, Azure, Google Cloud) and hybrid cloud solutions. - Orchestration & Tooling: Knowledge of software-defined infrastructure, Kubernetes, and MLOps technologies. - Advanced Cooling: Experience with liquid cooling technologies and practices. - Systems & Networking: Hands-on experience with InfiniBand, NVIDIA Networking technologies (DPU, RoCE), and ARM CPU solutions. - Programming: Experience with Python or C/C++ programming and AI workflow development (training/inference). ## Benefits NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all.