AI and FSI Developer Technology Engineer - New College Grad 2026
About the role
The AI Developer Technology Engineer position at NVIDIA focuses on accelerating high-performance workloads for financial services (FSI) using AI on both NVIDIA CPUs and GPUs. This role involves researching, designing, and developing groundbreaking techniques, analyzing, optimizing, and scaling complex AI and HPC workloads, profiling and eliminating performance bottlenecks, publishing and presenting findings, and influencing future hardware and software designs.
Responsibilities
- Researching, designing, and developing techniques to accelerate high-performance workloads for FSI-focused AI on NVIDIA CPUs and GPUs.
- Working 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 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
- Pursuing or recently completed a Master’s or PhD degree (or equivalent experience) in Computer Science, Computer Engineering, or Electrical and Computer Engineering or related field.
- Relevant work or research experience.
- Experience with low-level parallel programming (e.g., CUDA).
- Deep understanding of CPU/GPU architecture fundamentals and how they impact performance.
- Fluency in C/C++ and solid foundations in algorithms and software design.
- Experience improving the performance of large-scale computational applications on GPUs.
- Good understanding of linear algebra.
- Strong communication and organization skills, with a logical approach to problem solving and solid prioritization abilities.
Qualifications
- Prior internship experience in a related field.
- 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, and knowledge of financial data models, pricing and risk simulation algorithms, portfolio optimization, or other finance-focused applications and services.
Skills
- Experience with low-level parallel programming (e.g., CUDA).
- Understanding of CPU/GPU architecture fundamentals and their impact on performance.
- Fluency in C/C++ and strong foundations in algorithms and software design.
- Experience in optimizing large-scale computational applications on GPUs.
- Good understanding of linear algebra.
- Strong communication and organization skills, with a logical approach to problem-solving and solid prioritization abilities.
Benefits
NVIDIA offers competitive compensation packages including base salary ranging from $124,000 to $195,500 for Level 2 and $152,000 to $241,500 for Level 3, along with equity and benefits.
Pay
Base salary range: $124,000 - $195,500 for Level 2, and $152,000 - $241,500 for Level 3.
Schedule
Full-time employment.
Benefits
Eligibility for equity and comprehensive benefits package.
Application Instructions
Applications for this job will be accepted at least until April 13, 2026.
Company Information
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. We highly value diversity in our current and future employees and 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.