Senior AI and FSI Developer Technology Engineer

NVIDIA•Us, CA

6d•Hybrid

About The Position

Help shape the future of AI and LLMs in FSI (Financial Services Industry) at NVIDIA! We’re looking for a Senior AI Developer Technology Engineer to push the limits of performance at the intersection of AI, high-performance computing, and financial markets! In this role, you’ll dive deep into parallel algorithms, GPUs, and sophisticated systems, identifying and eliminating bottlenecks to unlock the full power of the most advanced processing hardware in the world. You’ll collaborate with top experts across industry and academia, influence next-generation platforms, and share your insights with the global developer community. Would you enjoy solving hard technical problems, love performance tuning, and want your work to have a visible impact across an entire industry? If so, we would love to invite you to consider this role. 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!

Requirements

Master’s or PhD in Computer Science, Computer Engineering, or Electrical and Computer Engineering (or equivalent experience).
Strong, hands-on experience with low-level parallel programming (e.g., CUDA, OpenACC, OpenMP, MPI, pthreads, TBB, etc.).
Deep understanding of CPU/GPU architecture fundamentals and how they impact performance.
Fluency in C/C++ and solid foundations in algorithms and software design.
5+ years of relevant work or research experience.
Proven experience improving the performance of large-scale computational applications on GPUs.
Excellent understanding of linear algebra.
Strong communication and organization skills, with a logical approach to problem solving and solid prioritization abilities.

Nice To Haves

Experience with inference optimization techniques and deploying optimized AI models in production.
Experience with TensorRT, TensorRT-LLM, and cuTile.
Background in capital markets with exposure to systematic/algorithmic strategies or quantitative trading.
Experience parallelizing and optimizing machine learning methods such as decision trees, time series models, and Monte Carlo simulations.
Knowledge of financial data models, pricing and risk simulation algorithms, portfolio optimization, or other finance-focused applications and services.

Responsibilities

Researching, designing, and developing groundbreaking techniques to accelerate high-performance workloads for FSI-focused, pioneering AI on NVIDIA CPUs and GPUs.
Working hands-on with leading technical experts to analyze, optimize, and scale complex AI and HPC workloads for modern CPU and GPU architectures.
Profiling and eliminating performance bottlenecks across the stack: from algorithms to kernels to system-level behavior.
Publishing and presenting your work in conferences, talks, and blogs to educate and inspire the broader developer community.
Influencing the design of future hardware architectures, system software, libraries, and programming models by collaborating closely with NVIDIA research, hardware, compiler, and tools teams.