1

Internship Nvidia Engineering Jobs in Hackensack, NJ

Build AI integrations on AWS, Azure, or NVIDIA tooling--and with open-source models--favoring ... Engineering, or a related field. * Experience: Up to 2 years of practical experience (internships ...

Build AI integrations on AWS, Azure, or NVIDIA tooling-and with open-source models-favoring ... Engineering, or a related field. * Experience: Up to 2 years of practical experience (internships ...

Build AI integrations on AWS, Azure, or NVIDIA tooling-and with open-source models-favoring ... Engineering, or a related field. * Experience: Up to 2 years of practical experience (internships ...

Build AI integrations on AWS, Azure, or NVIDIA tooling--and with open-source models--favoring ... Engineering, or a related field. * Experience: Up to 2 years of practical experience (internships ...

ML Infrastructure Engineer, Fauna

New York, NY · On-site

$117K - $154K/yr

... hardware (NVIDIA Jetson) with strict latency and memory constraints Build and maintain MLOps ... BASIC QUALIFICATIONS - 5+ years of non-internship professional software development experience - 5+ ...

Internship Nvidia Engineering information

See Hackensack, NJ salary details

$12

$21

$32

How much do internship nvidia engineering jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for internship nvidia engineering in Hackensack, NJ is $21.07, according to ZipRecruiter salary data. Most workers in this role earn between $17.55 and $22.79 per hour, depending on experience, location, and employer.

What is the difference between Internship Nvidia Engineering vs Software Engineering Intern?

AspectInternship Nvidia EngineeringSoftware Engineering Intern
Required CredentialsEnrolled in Computer Science or related field, strong programming skillsEnrolled in Computer Science or related field, coding proficiency
Work EnvironmentResearch labs, hardware and software development teams at NvidiaSoftware development teams, tech companies or startups
Employer & Industry UsageNvidia, semiconductor and AI industryTech companies, software firms, startups
Common Search & ComparisonInternship Nvidia Engineering vs Software Engineering Intern

Internship Nvidia Engineering focuses on hardware, AI, and graphics technology within Nvidia's innovative environment, while Software Engineering Internships are broader, covering various software development roles across multiple tech companies. Both require programming skills and relevant coursework, but Nvidia internships emphasize hardware-software integration and AI applications.

Infographic showing various Internship Nvidia Engineering job openings in Hackensack, NJ as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $43,816 per year, or $21.1 per hour.

AI and FSI Developer Technology Engineer- New College Grad 2026

Nvidia

New York, NY • On-site

Full-time

Re-posted 29 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies


Job description

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA's GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team!

We're looking for an 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 complex systems to identify and eliminate bottlenecks, unlocking the full power of the world's most advanced processing hardware. 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!

What you will be doing:

  • Researching, designing, and developing groundbreaking techniques to accelerate high-performance workloads for FSI-focused, pioneering 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 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.

What we need to see:

  • 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.

Ways to stand out from the crowd:

  • 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 as well as knowledge of financial data models, pricing and risk simulation algorithms, portfolio optimization, or other finance-focused applications and services.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 13, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993