AI and FSI Developer Technology Engineer - New College Grad 2026

at Nvidia

📍 Santa Clara, United States

USD 124,000-241,500 per year

JUNIOR MIDDLE

✅ On-site

Used Tools & Technologies

Not specified

Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Algorithms @ 3 Hiring @ 3 Communication @ 6 Parallel Programming @ 3 Prioritization @ 6 LLM @ 3 CUDA @ 3 GPU @ 3 Deep Learning @ 3 AI @ 3 TensorRT @ 3 HPC @ 3

Details

Work at NVIDIA is focused on visual and AI computing. NVIDIA pioneered visual computing with the GPU and today GPUs are used to run deep learning algorithms across many domains. This role sits at the intersection of AI, high-performance computing (HPC), and financial markets (FSI). You'll dive deep into parallel algorithms, GPUs, and complex systems to identify and eliminate bottlenecks, unlocking the performance of modern CPU and GPU hardware. You will collaborate with experts across industry and academia and share your findings with the global developer community.

Responsibilities

Research, design, and develop techniques to accelerate high-performance workloads for FSI-focused AI on NVIDIA CPUs and GPUs.
Analyze, optimize, and scale complex AI and HPC workloads for modern CPU and GPU architectures together with technical experts.
Profile and eliminate performance bottlenecks across the stack: algorithms, kernels, and system-level behavior.
Publish and present work in conferences, talks, and blogs to educate and inspire the developer community.
Influence the design of future hardware architectures, system software, libraries, and programming models by collaborating with NVIDIA research, hardware, compiler, and tools teams.

Requirements

Pursuing or recently completed a Master's or PhD (or equivalent experience) in Computer Science, Computer Engineering, Electrical and Computer Engineering, or a 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, logical problem solving, and prioritization abilities.

Ways to stand out

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 methods such as decision trees, time series models, and Monte Carlo simulations; knowledge of financial data models, pricing and risk simulation algorithms, or portfolio optimization.

Compensation & Benefits

Base salary ranges by level:
- Level 2: 124,000 USD - 195,500 USD
- Level 3: 152,000 USD - 241,500 USD
Eligible for equity and benefits (link to NVIDIA benefits in original posting).

Additional information

Applications accepted at least until April 13, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is an equal opportunity employer and committed to diversity in hiring and promotion practices.