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Remote Nvidia Engineering Jobs in Chicago, IL (NOW HIRING)

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

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GPU Programmer - Remote

Chicago, IL ยท Remote

$60 - $85/hr

Strong experience with GPU programming, particularly on NVIDIA GPUs . * Proficiency in CUDA, WebGPU, or GLSL . * Strong C++ programming skills. * Background in graphics programming, ML acceleration ...

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Strong experience with GPU programming, particularly on NVIDIA GPUs . * Proficiency in CUDA, WebGPU, or GLSL . * Strong C++ programming skills. * Background in graphics programming, ML acceleration ...

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CUDA Developer - Remote

Chicago, IL ยท Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

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CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

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Senior Machine Learning Engineer

Chicago, IL ยท Remote

$165K - $225K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... Knowledge of software engineering best practices including version control (Git) and CI/CD ...

Their team includes engineers from Waymo, Cruise, Apple, NVIDIA, and Google. They are fully remote and growing fast. How long has the company been operating? 2017 Total company headcount: 50 ...

Enterprise Account Executive

Chicago, IL ยท Remote

$280K - $330K/yr

You will be selling a technical platform that solves critical problems for Engineering, DevOps, ... and we have a remote-first work culture. We are the leading platform for operating GPU ...

Remote Nvidia Engineering information

See Chicago, IL salary details

$58.7K

$141.1K

$202.9K

How much do remote nvidia engineering jobs pay per year?

As of Aug 22, 2026, the average yearly pay for remote nvidia engineering in Chicago, IL is $141,136.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,200.00 and $156,100.00 per year, depending on experience, location, and employer.

What is a remote Nvidia engineer?

A Remote Nvidia Engineer is a professional who works for Nvidia, or with Nvidia technologies, from a location outside of a traditional office setting. These engineers may specialize in areas such as GPU development, AI research, software engineering, or hardware design, and they collaborate with teams virtually. Remote Nvidia Engineers use digital tools to communicate, manage projects, and contribute to cutting-edge technologies in graphics processing, artificial intelligence, and computing platforms. The remote aspect allows for flexible work arrangements and the ability to participate in global projects.

What are the key skills and qualifications needed to thrive as a remote Nvidia engineer, and why are they important?

To excel as a Remote Nvidia Engineer, you typically need a strong background in computer engineering, programming (e.g., C++, Python), and experience with GPU architectures, often supported by a relevant degree. Familiarity with Nvidia tools like CUDA, cuDNN, and deep learning frameworks, as well as proficiency in remote collaboration platforms, are crucial. Strong problem-solving skills, self-motivation, and effective communication are vital soft skills for working independently and collaborating across distributed teams. These competencies ensure efficient development, troubleshooting, and innovation in Nvidia's complex, high-performance computing environments.

What are some common challenges faced by engineers working remotely for Nvidia, and how can they be overcome?

Remote engineers at Nvidia often encounter challenges related to communication across time zones, staying aligned with fast-paced project developments, and maintaining visibility within distributed teams. To overcome these, it's important to proactively engage in virtual meetings, leverage collaboration tools like Slack and Jira, and regularly update your team on progress. Building strong relationships with peers and seeking out mentorship opportunities can also help remote engineers stay connected and advance within the company.

What is the difference between Remote Nvidia Engineering vs Remote Nvidia Data Scientist?

AspectRemote Nvidia EngineeringRemote Nvidia Data Scientist
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with GPU programmingBachelor's or higher in Data Science, Statistics, or related; proficiency in machine learning and data analysis
Work EnvironmentDesign, develop, and optimize GPU hardware/software; collaborative teamsAnalyze large datasets, develop models, and generate insights; often cross-functional teams
Employer & Industry UsagePrimarily in hardware, AI, and high-performance computing sectorsPrimarily in AI, analytics, and research sectors

Remote Nvidia Engineering focuses on hardware and software development for GPUs, requiring engineering credentials and technical skills. Remote Nvidia Data Scientists analyze data and build models, requiring expertise in data science. Both roles are remote, but they serve different functions within Nvidia's ecosystem.

What are the most commonly searched types of Nvidia Engineering jobs in Chicago, IL?

The most popular types of Nvidia Engineering jobs in Chicago, IL are:

What job categories do people searching Remote Nvidia Engineering jobs in Chicago, IL look for?

The top searched job categories for Remote Nvidia Engineering jobs in Chicago, IL are:

CUDA Engineering Expert - Remote

YO AI Labs

Chicago, IL โ€ข Remote

$60 - $100/hr

Full-time

Posted yesterday

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Job description

CUDA Engineering Expert

Job Type: Contractor
Location: Remote

Job Overview

We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your expertise in CUDA, C++, and GPU programming to analyze, optimize, and improve high-performance GPU kernels.

No prior AI experience is required.

Key Responsibilities
  • Analyze, profile, and optimize GPU kernels using CUDA and profiling tools.

  • Identify performance bottlenecks and develop targeted optimization strategies.

  • Refactor C++ and CUDA code for efficiency and maintainability.

  • Develop shader logic using GLSL and WebGPU.

  • Document optimization processes, findings, and performance improvements.

  • Contribute to GPU architecture and performance discussions.

  • Collaborate with remote, cross-functional teams.

Required Qualifications
  • Strong expertise in CUDA programming and GPU kernel optimization.

  • Advanced C++ development skills.

  • Hands-on experience with GLSL and WebGPU.

  • Experience using GPU profiling tools such as NVIDIA Nsight or similar.

  • Strong understanding of GPU performance and architecture.

  • Excellent analytical, problem-solving, and technical communication skills.

  • Ability to work effectively in a remote environment.

Preferred Qualifications
  • Experience with high-performance computing or GPU-accelerated applications.

  • Experience optimizing workloads across different GPU architectures.

  • Background in graphics, compute shaders, or AI/ML acceleration.