Senior AI Developer Technology Engineer, Financial Sector

NVIDIA•Santa Clara, CA

1d•Hybrid

About The Position

We’re currently seeking a Senior 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 to investigate, find, and eliminate system bottlenecks 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. What you will be doing: 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. What we need to see: An advanced degree in Computer Science, Computer Engineering, or related computationally focused science degree (or equivalent experience). You have 5+ years of relevant work or research experience. Direct experience improving the performance of large computational applications used by financial institutions. Excellent 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. In-depth expertise with CPU/GPU architecture fundamentals. Good communication and organization skills, with a logical approach to problem solving, and prioritization skills. Ways to stand out from the crowd: 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 DevTech Engineer plays a crucial role in the success of NVIDIA and our customers. DevTechs 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 you are a leading industry luminary or early in your career, the Developer Technology Team provides ample opportunity for growth in the exciting field of GPU-accelerated computing! #LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until February 22, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. NVIDIA is the world leader in accelerated computing. NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society. Learn more about NVIDIA.

Requirements

An advanced degree in Computer Science, Computer Engineering, or related computationally focused science degree (or equivalent experience).
You have 5+ years of relevant work or research experience.
Direct experience improving the performance of large computational applications used by financial institutions.
Excellent 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.
In-depth expertise with CPU/GPU architecture fundamentals.
Good communication and organization skills, with a logical approach to problem solving, and prioritization skills.

Nice To Haves

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.

Responsibilities

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.