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Remote Gpu Jobs (NOW HIRING)

The role We are looking for a Customer Engineer to support key and strategic Nebius GPU Cloud ... Remote Work Reimbursement: Up to $85/month for mobile and internet. * Disability & Life Insurance:

AI Cluster Architect

$65 - $89/hr

... first year remote office setup + $400 each following year for new equipment * Internet ... The architect must understand how different GPU SKUs, NICs, switches, and fabrics interact at scale ...

... a single GPU to multi-region GPU clusters in the cloud * Automate data ingest and feature ... Experience with numerical weather prediction, remote-sensing data, or geospatial intelligence

US East/Canada (Remote) Role Overview: We are looking for a highly skilled Architect - Platform ... Perform GPU profiling, benchmarking, and performance optimization for distributed training ...

We own the design, operation, and reliability of hybrid GPU AI clusters that power frontier AI ... remote dev, containerization, MLOps workflows). What You'll Bring Essential * Bachelor's or ...

Senior Software Engineer - Topography

Santa Clara, CA · Remote

$143K - $189K/yr

Experience with GPU clusters, NVLink, InfiniBand, Ethernet fabrics, or HPC. * Hands-on work with ... If you're a creative, curious, and driven technical leader, we want to hear from you! #LI-Remote ...

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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.
More about Remote Gpu jobs
What cities are hiring for Remote Gpu jobs? Cities with the most Remote Gpu job openings:
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:
Senior Software Engineer AI Middleware

Senior Software Engineer AI Middleware

Cornelis Networks, Inc.

Austin, TX • Remote

$125K - $165K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 24 days ago


Job description

Salary:

At Cornelis were building the future of AI and HPC networking with an AI-first approach to silicon and software development. Were seeking engineers who are energized by working on cutting-edge ASIC design and distributed software systems, and who are motivated to push the boundaries on how AI can transform everything from chip architecture to system performance at scale.


Cornelis Networks delivers the worlds highest performance scale-out networking solutions for AI and HPC datacenters. Our differentiated architecture seamlessly integrates hardware, software and system level technologies to maximize the efficiency of GPU, CPU and accelerator-based compute clusters at any scale. Our solutions drive breakthroughs in AI & HPC workloads, empowering our customers to push the boundaries of innovation. Backed by top-tier venture capital and strategic investors, we are committed to innovation, performance and scalability - solving the worlds most demanding computational challenges with our next-generation networking solutions.


We are a fast-growing, forward-thinking team of architects, engineers, and business professionals with a proven track record of building successful products and companies. As a global organization, our team spans multiple U.S. states and six countries, and we continue to expand with exceptional talent in onsite, hybrid, and fully remote roles.


We are seeking a highly experienced Senior Software Engineer to design, develop, and upstream-enable Cornelis Networks AI communication middleware. This role focuses on distributed AI workloads and enabling/optimizing collective communication libraries (e.g., NCCL/RCCL) over Cornelis Networks interconnects.


Key Responsibilities

  • Design and implement performance-critical features for CCL enablement on Cornelis Networks fabrics.
  • Optimize distributed training performance across multi-node, multi-GPU configurations.
  • Improve GPU communication paths including GPU-direct transfers, IPC, and CPU/GPU synchronization.
  • Profile distributed AI workloads and identify bottlenecks across the software and hardware stack.
  • Tune AI frameworks such as PyTorch Distributed, TensorFlow/XLA, JAX, DeepSpeed, and Megatron-LM.
  • Develop benchmarks and microbenchmarks aligned with real model performance.
  • Contribute upstream to AI communication and distributed training projects.
  • Participate in design reviews, code reviews, CI, and long-term maintenance.
  • Prototype and validate Ultra Ethernet capabilities for AI collective communication.
  • Provide technical input for deployment considerations and performance validation.
  • Collaborate with kernel/driver, switch, performance, and systems teams.
  • Support advanced escalations by analyzing traces and providing robust fixes.


Minimum Qualifications

  • 8+ years of experience in high-performance systems programming in C/C++ on Linux.
  • Strong experience with GPU communication stacks including CUDA/ROCm and NCCL/RCCL.
  • Ability to optimize distributed training performance using profiling and tracing.
  • Understanding of collective communication concepts and topology awareness.
  • Experience delivering production-quality code.
  • Open-source contributions in relevant areas.


Preferred Qualifications

  • Experience with AI frameworks such as PyTorch Distributed, DeepSpeed, and Megatron-LM.
  • Familiarity with libfabric/OFI, UCX, and RDMA concepts.
  • Experience with RoCEv2 and Ultra Ethernet.
  • Experience building cluster-scale performance test infrastructure.


Location:This is a remote position for employees residing within the United States.


We offer a competitive compensation package that includes equity, cash, and incentives, along with health and retirement benefits. Our dynamic, flexible work environment provides the opportunity to collaborate with some of the most influential names in the semiconductor industry.


At Cornelis Networks your base salary is only one component of your comprehensive total rewards package. Your base pay will be determined by factors such as your skills, qualifications, experience, and location relative to the hiring range for the position. Depending on your role, you may also be eligible for performance-based incentives, including an annual bonus or sales incentives.

In addition to your base pay, youll have access to a broad range of benefits, including medical, dental, and vision coverage, as well as disability and life insurance, a dependent care flexible spending account, accidental injury insurance, and pet insurance. We also offer generous paid holidays, 401(k) with company match, and Open Time Off (OTO) for regular full-time exempt employees. Other paid time off benefits include sick time, bonding leave, and pregnancy disability leave.


Cornelis Networks does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. Cornelis Networks is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants needs under the respective laws throughout all stages of the recruitment and selection process.