Senior AI and FSI Developer Technology Engineer

About the role

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!

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.

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.

Qualifications

• 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.

Skills

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.

Benefits

Base salary range: $152,000 - $241,500 for Level 3, and $184,000 - $287,500 for Level 4.
Eligible for equity and benefits.

Pay

Base salary will be determined based on your location, experience, and the pay of employees in similar positions.

Schedule

Not specified.