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Remote Gpu Jobs (NOW HIRING)

$135K - $181K/yr

Design and evolve a unified memory layer that spans GPU memory, pinned host memory, RDMA-accessible memory, SSD tiers, and remote file/object/cloud storage to support large-scale LLM inference.

As Runpod continues to revolutionize the GPU cloud computing landscape, we are seeking a full-time, remote Security Engineer to join our team. This critical position will be instrumental in ...

Senior Software Engineer - CUDA

Palo Alto, CA · On-site +1

$144K - $189K/yr

Through the application of folding schemes, proof aggregation, and GPU acceleration, we're pushing ... A flexible and innovative remote work environment. * Room for continuous growth and development in ...

Senior Software Engineer - CUDA

Palo Alto, CA · On-site +1

$144K - $189K/yr

Through the application of folding schemes, proof aggregation, and GPU acceleration, we're pushing ... A flexible and innovative remote work environment. * Room for continuous growth and development in ...

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Remote Gpu information

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 a strong background in computer science, GPU architectures, parallel programming (CUDA/OpenCL), and relevant software development experience. Familiarity with tools like NVIDIA CUDA Toolkit, profiling/debugging utilities, and cloud-based GPU platforms (e.g., AWS, Azure) is essential, along with certifications in GPU computing as a plus. Excellent problem-solving, communication, and self-motivation are critical soft skills for collaborating remotely and handling complex technical challenges. Mastery of these skills ensures efficient design, optimization, and deployment of high-performance GPU solutions in distributed environments.

What are Remote GPUs?

Remote GPUs are graphics processing units that are hosted on remote servers and accessed over the internet, rather than being physically installed in your local computer. They enable users to perform high-performance computing tasks such as machine learning, rendering, or data analysis without investing in expensive hardware. Remote GPUs are commonly used in cloud computing environments, making powerful GPU resources accessible on-demand and scalable according to project needs.

What is the difference between Remote Gpu vs Remote Data Scientist?

AspectRemote GpuRemote Data Scientist
Required CredentialsGPU programming certifications, CUDA, OpenCLStatistics, machine learning, programming (Python, R)
Work EnvironmentHigh-performance computing, hardware access, cloud GPU servicesData analysis, modeling, visualization
Industry UsageAI, deep learning, graphics renderingBusiness analytics, research, AI development

Remote Gpu roles focus on GPU programming and hardware utilization for AI and graphics tasks, often requiring technical certifications. Remote Data Scientists analyze data, build models, and interpret results, typically with programming and statistical skills. While both roles may work remotely and in tech industries, their core skills and tools differ significantly.

What are some common challenges faced by professionals working in Remote GPU roles, and how can they be addressed?

Professionals in Remote GPU roles often encounter challenges such as managing latency, ensuring data security, and optimizing resource allocation across distributed systems. Effective communication and collaboration with cross-functional teams—including software developers, data scientists, and IT administrators—are essential to address these issues. Staying updated with the latest GPU virtualization technologies and best practices can also help professionals troubleshoot performance bottlenecks and maintain seamless remote access to GPU resources.
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What are the most commonly searched types of Gpu jobs? The most popular types of Gpu jobs are:
What states have the most Remote Gpu jobs? States with the most job openings for Remote Gpu jobs include:
MLOPs Lead Location:- Remote Duration:- Full Time

MLOPs Lead Location:- Remote Duration:- Full Time

Siri InfoSolutions Inc

Atlanta, GA • Remote

$60.50 - $79/hr

Full-time

Posted 13 days ago

Be an early applicant


Job description

MLOPs Lead

Location:- Remote

Duration:- Full Time

Job Description

  • Python, Model Engg on Pytorch, Tensorflow, TFX, Flask, TorchServing, GCP (Google Cloud Platform), Vertex AI and Kubeflow
  • Experience in AI/ML more than 5 years.
  • Minimum 3 years’ experience played as a ML ops
  • Good to Have: Knowledge in GPU programming, GPU profiling, GPU optimizations & TensorRT

Roles & Responsibilities:

  • Meeting with Client team to understand the requirements and opportunities.
  • Provides management with timely communication on status & utilizes appropriate tools and/or develops custom solutions as required to meet objectives. o Identifies areas for process improvement.
  • Maintains appropriate communication within the team and across various teams (i.e., internal and external). Strong analytical ability o Excellent oral and written communication skills is a must. 

Siri Infosolutions logo

About Siri Infosolutions

Sourced by ZipRecruiter

Our team of experts first gather each and every requirement of yours. Our research and development team then sit around those requirements and come up with a plan. Our implementation team then executes that plan for optimal results. After that our support team remains in constant touch with you during and after the entire process.

Industry

It services

Company size

201 - 500 Employees

Headquarters location

Edison, NJ, US

Year founded

2005