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Remote Gpu Engineer Jobs in Rutherford, NJ (NOW HIRING)

vCluster Labs

Enterprise Account Executive

New York, NY · 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 ...

New

vCluster Labs

Enterprise Account Executive

New York, NY · 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 ...

New

Career Renew

Senior Machine Learning Engineer

New York, NY · Remote

$165K - $225K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX export, and ...

Invoca

Senior ML Engineer

New York, NY · On-site +1

$114K - $157K/yr

... GPU infrastructure. Profile and tune for low latency and high throughput, and build robust ... Familiarity with RLHF or preference training is a bonus 📍 Location This is a remote-first role.

Nvidia

Senior Software Engineer - Agentic Memory

New York, NY · On-site +1

$134K - $176K/yr

... remote work is accepted. GPU computing is the most productive and pervasive platform for deep ... If you're a creative engineer who enjoys autonomy and shares our passion for technology, we want to ...

Nebius

RVP, Digital Sales

New York, NY · Remote

Our GTM leadership team operates with high trust, direct access to Product and Engineering, and the ... Evangelize Nebius's NVIDIA-based GPU platform (H100, H200, B200, GB200 NVL72, and beyond) for ...

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Remote Gpu Engineer information

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$25

$54

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How much do remote gpu engineer jobs pay per hour?

As of Jul 2, 2026, the average hourly pay for remote gpu engineer in Rutherford, NJ is $54.67, according to ZipRecruiter salary data. Most workers in this role earn between $44.09 and $63.46 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote GPU Engineer, and why are they important?

To thrive as a Remote GPU Engineer, you need strong expertise in GPU architectures, parallel programming (CUDA/OpenCL), and a solid background in computer science or engineering. Familiarity with tools like CUDA Toolkit, performance profilers, and version control systems, as well as experience with relevant certifications, is typically required. Excellent problem-solving abilities, communication skills, and the capacity to collaborate effectively in remote, distributed teams are standout soft skills. These competencies ensure efficient GPU solution development, effective troubleshooting, and seamless teamwork in a remote engineering environment.

What are Remote GPU Engineers?

Remote GPU Engineers are specialized software or hardware engineers who work primarily with Graphics Processing Units (GPUs) from a remote location. They focus on designing, optimizing, and maintaining GPU-based systems for applications such as machine learning, high-performance computing, and graphics rendering. These professionals often collaborate with teams virtually, leveraging cloud-based GPU resources and remote access tools. Their work enables companies to efficiently utilize GPU technology without requiring engineers to be on-site.

What are some common challenges faced by Remote GPU Engineers when collaborating with distributed teams?

Remote GPU Engineers often work with global teams, which can present challenges such as coordinating across different time zones, ensuring consistent communication, and managing access to high-performance hardware remotely. To overcome these hurdles, it's important to leverage collaboration tools, maintain clear documentation, and establish regular check-ins. Additionally, using remote desktop solutions and cloud-based GPU environments can help facilitate smoother development and debugging processes.
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Remote Gpu Engineer jobs near you
Open-Source Machine Learning Engineer - US Remote

Open-Source Machine Learning Engineer - US Remote

Hugging Face

New York, NY • Remote

Full-time

Posted 3 days ago

Job description

At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 million datasets & 1.5 million Gradio apps. Our open-source libraries have more than 700,000 stars on Github.

About the Role

As an Open-Source Machine Learning Engineer, you'll work to improve the open-source machine learning ecosystem. You'll mainly work on existing open-source libraries such as Transformers, Datasets, Pytorch and vLLM, and you'll interact with users and contributors across the broad open-source ML ecosystem. We'll brainstorm with you to put you in a position to do the work that interests you and that is impactful.

You'll help foster one of the most active machine learning communities, helping users contribute to and use the tools you build. You'll work with researchers, ML practitioners, and data scientists every day through GitHub, our forums, and Slack.

About You

You have a public track record of open-source work, and you enjoy collaborating with a community out in the open on GitHub. You love open source, you're passionate about making complex technology more accessible, and you want to contribute to one of the fastest-growing ML ecosystems. If that's you, we can't wait to see your application.

What you'll need
  • Strong Python skills, with experience writing clean, well-tested, maintainable library code
  • Deep hands-on experience with a modern deep-learning framework, especially PyTorch (JAX or TensorFlow a plus)
  • Practical experience with the Hugging Face open-source stack (Transformers, Datasets, Accelerate) or comparable ML libraries
  • A public track record of open-source contributions, for example merged pull requests to ML or data libraries, that we can review on GitHub
  • Solid understanding of modern machine learning and deep learning, including transformer architectures
  • Experience collaborating with a technical community in the open (GitHub issues and reviews, forums, Slack or Discord)
  • Fluent written English for asynchronous collaboration across a distributed, global community
Nice to have
  • Experience maintaining an open-source project
  • Prior contributions to Transformers, Datasets, Accelerate, or similar libraries
  • Familiarity with distributed training, inference optimization, or GPU/accelerator performance work
  • Experience training or fine-tuning models at scale
A note on fit

If you're interested in joining us but don't tick every box above, we still encourage you to apply. We're building a diverse team whose skills, experiences, and backgrounds complement one another, and we're happy to consider where you might make the biggest impact.

One more thing

At Hugging Face we believe great AI shouldn't require a massive cluster, we build for everyone, especially the GPU-poor. And because we read every application, here's a small sign that you read this one too: start your answer to the first application question with the words “GPU-poor and proud