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Remote Nvidia Deep Learning Jobs (NOW HIRING)

Senior Compiler Engineer Infrastructure

Austin, TX ยท On-site +1

$107.50K - $146.20K/yr

Familiarity with deep learning frameworks and performance-sensitive workloads on NVIDIA GPUs With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be ...

Senior Machine Learning Engineer

Chicago, IL ยท Remote

$165K - $225K/yr

The ideal candidate will have deep expertise in Machine Learning and building generalizable ... NVIDIA DGX Spark. Understanding of FDA regulatory requirements for AI/ML in medical devices ...

Senior Machine Learning Engineer

Atlanta, GA ยท Remote

$165K - $225K/yr

The ideal candidate will have deep expertise in Machine Learning and building generalizable ... NVIDIA DGX Spark. Understanding of FDA regulatory requirements for AI/ML in medical devices ...

Technical Architect - Machine Learning

OR ยท Remote

$66.25 - $80/hr

Remote (USA/Canada) Description: As an Architect - Machine Learning Engineer at Quantiphi, you will ... Should have experience with Deep Learning Concepts - Transformers, BERT, Attention models * Strong ...

Technical Architect - Machine Learning

$67.75 - $82/hr

Remote (USA/Canada) Description: As an Architect - Machine Learning Engineer at Quantiphi, you will ... Should have experience with Deep Learning Concepts - Transformers, BERT, Attention models * Strong ...

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Remote Nvidia Deep Learning information

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$11K

$83.9K

$140K

How much do remote nvidia deep learning jobs pay per year?

As of May 31, 2026, the average yearly pay for remote nvidia deep learning in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is the difference between Remote Nvidia Deep Learning vs Remote Machine Learning Engineer?

AspectRemote Nvidia Deep LearningRemote Machine Learning Engineer
Required CredentialsDeep learning certifications, Nvidia GPU expertise, programming skills in Python and CUDAMachine learning certifications, Python, data analysis, model deployment skills
Work EnvironmentRemote, GPU-intensive tasks, AI research, model trainingRemote, data processing, model development, deployment
Industry UsageAI research labs, tech companies, autonomous vehiclesTech firms, finance, healthcare, e-commerce

Remote Nvidia Deep Learning focuses on developing AI models using Nvidia GPUs and CUDA, often in research or AI-specific roles. Remote Machine Learning Engineers work on building and deploying machine learning models across various industries. While both roles require programming and data skills, Nvidia Deep Learning emphasizes GPU expertise and AI research, whereas Machine Learning Engineers focus on broader model deployment and application.

More about Remote Nvidia Deep Learning jobs
What cities are hiring for Remote Nvidia Deep Learning jobs? Cities with the most Remote Nvidia Deep Learning job openings:
What are the most commonly searched types of Nvidia Deep Learning jobs? The most popular types of Nvidia Deep Learning jobs are:
What states have the most Remote Nvidia Deep Learning jobs? States with the most job openings for Remote Nvidia Deep Learning jobs include:
Infographic showing various Remote Nvidia Deep Learning job openings in the United States as of May 2026, with employment types broken down into 79% Full Time, and 21% Part Time. Highlights an 73% Physical, 1% Hybrid, and 26% Remote job distribution, with an average salary of $83,885 per year, or $40.3 per hour.
Senior Compiler Engineer Infrastructure

Senior Compiler Engineer Infrastructure

Nvidia

Austin, TX โ€ข On-site, Remote

$107.50K - $146.20K/yr

Full-time

Posted 23 days ago


Job description

Come join the team and see how you can make a lasting impact on the world. We are looking for an experienced Compiler Infrastructure Engineer to join our Compute Compiler Team, with a primary focus on aligning NVIDIA's compiler codebases with open-source ecosystems and improving developer productivity at scale. This role sits at the intersection of open-source compiler development, internal compiler infrastructure, and developer experience. You will play a central role in reconciling downstream compiler repositories with upstream open-source projects such as LLVM, Clang, and MLIR, while building the tooling, workflows, and infrastructure that enable compiler engineers across NVIDIA to move faster and with higher confidence.

Our compiler organization makes its mark on every GPU NVIDIA produces. By improving how our internal compiler stacks align with open source and by modernizing the tools our developers rely on, you will help ensure that NVIDIA continues to lead in scalable, maintainable, and communitydriven compiler technology. If you are passionate about open-source stewardship, large-scale codebase alignment, and using modern tooling (including AI-assisted workflows) to improve developer velocity, we would love to hear from you.

What you will be doing:

  • Reconcile and synchronize downstream compiler codebases with open-source repositories, including restructuring, refactoring, and upstreaming internal changes where appropriate

  • Lead efforts to restructure, merge, or retire internal code to reduce divergence from upstream open-source projects

  • Design and build infrastructure, tooling, and developer workflows that improve productivity, correctness, and maintainability for internal compiler engineers

  • Develop automation and developer tools to aid in rebasing, patch management, validation, and large-scale refactoring

  • Explore and apply AI-assisted tools to improve developer workflows, including code navigation, change analysis, refactoring assistance, testing, and review efficiency

  • Partner with compiler developers, architecture teams, and CI/test infrastructure teams to ensure changes scale across geographically distributed organizations

  • Serve as a technical bridge between internal compiler development and open-source ecosystems, helping shape long-term alignment strategies

What we need to see:

  • B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or related field (or equivalent experience)

  • Experience with open-source compiler frameworks

  • Excellent hands-on C++ programming skills

  • 3+ years experience working with large-scale, long-lived codebases, including refactoring and restructuring efforts

  • Solid understanding of compiler internals, including IRs, passes, build systems, and toolchains

  • Familiarity with source-control-heavy workflows (e.g., downstream vs. upstream repos, patch queues, rebasing strategies)

  • Strong software engineering fundamentals with an emphasis on robust, maintainable developer infrastructure

  • Good communication and documentation skills; ability to collaborate across teams and time zones

Ways to stand out from the crowd:

  • Direct experience reconciling or maintaining downstream forks of open-source projects

  • Experience building developer productivity tools, CI infrastructure, or large-scale automation

  • Practical experience applying AI or ML-based tools to improve engineering workflows

  • Background in GPU programming, CUDA, or parallel programming models

  • Familiarity with deep learning frameworks and performance-sensitive workloads on NVIDIA GPUs

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.

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

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 11, 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.

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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