AI and FSI Developer Technology Engineer - New College Grad 2026

at Nvidia

USD 124,000-241,500 per year

JUNIOR

✅ On-site

Tech Stack
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.

AI @ 3 Algorithms @ 5 CUDA @ 3 Communication @ 6 GPU @ 6 HPC LLM @ 3 Parallel Programming @ 3 Performance Optimization Prioritization @ 6 TensorRT @ 3

Details

NVIDIA is looking for an AI Developer Technology Engineer to work at the intersection of artificial intelligence, high-performance computing, and financial markets. The role focuses on parallel algorithms, GPUs, complex systems, and performance optimization to unlock the capabilities of NVIDIA CPUs and GPUs for financial-services and insurance workloads.

Responsibilities

Research, design, and develop techniques to accelerate high-performance workloads for financial-services and insurance-focused AI on NVIDIA CPUs and GPUs.
Analyze, optimize, and scale complex AI and high-performance computing workloads for modern CPU and GPU architectures.
Profile and eliminate performance bottlenecks across the stack, including algorithms, kernels, and system-level behavior.
Publish and present work at conferences, talks, and blogs to educate the broader developer community.
Collaborate with NVIDIA research, hardware, compiler, and tools teams to influence the design of future hardware architectures, system software, libraries, and programming models.

Requirements

Pursuing or recently completed a Master's or PhD degree, 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, such as CUDA.
Deep understanding of CPU and GPU architecture fundamentals and their impact on 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 organizational skills, a logical approach to problem-solving, and solid prioritization abilities.

Preferred 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, including exposure to systematic or 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.

Compensation and Benefits

The base salary range is USD 124,000–195,500 for Level 2 and USD 152,000–241,500 for Level 3. Employees are also eligible for equity and benefits.

Applications will be accepted at least until April 13, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is committed to providing an equal-opportunity work environment.