AI Developer Technology Engineer, Financial - College Grad , AI Developer Techno

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world.

We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team!

We’re currently seeking a AI Developer Technology Engineer, Financial Sector! Would you like to help shape the future of financial AI and data analytics by designing and optimizing parallel algorithms on cutting‑edge computing platforms?

Is it rewarding toinvestigate, find, and eliminate systembottlenecks to achieve the best possible performance of computer hardware?

Could you be thrilled about an opportunity to partner with the Developer community, working at the forefront of technology breakthroughs that contribute to the success of an industry leader like NVIDIA? If so, the Developer Technology Team invites you to consider this role.

• In this position, you will research and develop techniques to GPU‑accelerate high‑performance workloads at the intersection of AI and financial markets.
• Work directly with other technical experts in their fields (industry and academia) to perform in‑depth analysis and optimization of complex AI and HPC workloads to ensure the best possible performance on modern CPU and GPU architectures.
• Publish and present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the Developer community.
• Influence the design of next‑generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.

• Pursuing or recently completed a BS, MS or PhD in Computer Science, Computer Engineering, or related field (or equivalent experience).
• Relevant work or research experience.
• Experience improving the performance of large computational applications used by financial institutions.
• Understanding of linear algebra.
• Programming fluency in C/C++ with a deep understanding of algorithms and software design.
• Hands‑on experience with low‑level parallel programming, e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, TBB, etc.
• Experience with CPU/GPU architecture fundamentals.
• Good communication and organization skills, with a logical approach to problem solving, and prioritization skills.

• A Master’s or PhD in a relevant field is highly valued.
• Prior work experience in capital markets with exposure to systematic/algorithmic strategies and quantitative trading.
• Experience with parallelizing and optimizing machine learning algorithms like decision trees, time series, and Monte Carlo simulations.
• Deep knowledge of financial data models, pricing/risk simulation algorithms, portfolio optimization, or other financial specific applications/ services.
• Have developed ML/DL techniques in the finance space, such as stock market prediction, fraud detection, portfolio optimization/selection.

The Dev Tech Engineer plays a crucial role in the success of NVIDIA and our customers. Dev Techs work with external technologists to investigate performance of their applications, design parallel algorithms and implement optimizations in a GPU accelerated computing environment. As recognized experts in the field we publish our findings in developer blogs or at relevant conferences and workshops. With insight to our customers, the industry, and academia we are important representatives of NVIDIA as a technology leader.

Within NVIDIA we contribute valuable application expertise that influences next generation hardware and software products. As critical problem solvers, we deepen our expertise, expand our knowledge, and work across domains and organizations. Whether…