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Cloud Gpu Jobs (NOW HIRING)

Vultr

GPU Solutions Engineer

With 33 global cloud data center locations, Vultr is trusted by hundreds of thousands of active customers across 185 countries for its flexible, scalable, global Cloud Compute, Cloud GPU, Bare Metal ...

Vultr

Strategic Technical Account Manager GPU

$115K - $140K/yr

With 33 global cloud data center locations, Vultr is trusted by hundreds of thousands of active customers across 185 countries for its flexible, scalable, global Cloud Compute, Cloud GPU, Bare Metal ...

Vultr

AI Cluster Architect

$65 - $89/hr

With 33 global cloud data center locations, Vultr is trusted by hundreds of thousands of active customers across 185 countries for its flexible, scalable, global Cloud Compute, Cloud GPU, Bare Metal ...

Dyna Robotics, Inc

$200 - $250/hr

The Role As a ML Training Infrastructure Engineer, you will architect and build the systems that turn our multi-cloud GPU fleet into a training engine our researchers love. Your charter is singular ...

General Robotics

Systems Engineer

Redmond, WA · On-site

$155K - $205K/yr

We build and optimize the infrastructure that powers generalized robotics foundation models - spanning edge devices to cloud GPU clusters - with a focus on low latency, high throughput, and efficient ...

Vultr

Senior Software Engineer, Cloud Networking

$128K - $145K/yr

With 33 global cloud data center locations, Vultr is trusted by hundreds of thousands of active customers across 185 countries for its flexible, scalable, global Cloud Compute, Cloud GPU, Bare Metal ...

Specter

Software Engineer - Applied AI

San Francisco, CA · On-site

$200 - $250/hr

Productionize models from the research team, spanning containerization, inference optimization, and deployment to edge devices and cloud GPU infrastructure. * Build and own offline and online ...

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Cloud Gpu information

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$10

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How much do cloud gpu jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for cloud gpu in the United States is $61.71, according to ZipRecruiter salary data. Most workers in this role earn between $54.09 and $74.04 per hour, depending on experience, location, and employer.

What is a cloud GPU?

Cloud GPU jobs refer to computational tasks that utilize Graphics Processing Units (GPUs) hosted on cloud platforms. These jobs can include machine learning, data analysis, graphics rendering, and scientific simulations, all executed remotely on powerful GPU hardware provided by cloud service providers. Using cloud GPUs allows users to scale their computing resources on demand without investing in expensive physical GPUs, making it cost-effective and flexible for businesses and researchers alike.

What skills and qualifications are needed to work with cloud GPUs?

To thrive as a Cloud GPU Engineer, you need a strong background in computer science, cloud computing, and GPU architecture, often supported by a degree in a relevant field and experience with parallel programming. Proficiency with cloud platforms (such as AWS, Azure, or Google Cloud), GPU management tools (like NVIDIA CUDA), and containerization systems (like Docker or Kubernetes) is typically required. Strong problem-solving skills, teamwork, and effective communication help you collaborate and address complex technical challenges. These skills and qualities are essential for optimizing GPU resources, ensuring high performance, and supporting scalable cloud-based solutions.

What are the main challenges faced when managing cloud GPU resources in a production environment?

One of the primary challenges in managing cloud GPU resources is optimizing usage to balance performance and cost, since GPUs can be expensive if left underutilized. Additionally, workloads often require careful scheduling and monitoring to ensure resource availability and prevent bottlenecks, especially when supporting multiple teams or projects. Security and data compliance can also be more complex due to the shared infrastructure in cloud environments. Collaborating effectively with DevOps, engineering, and data science teams is crucial to align resource allocation with project needs and timelines.

What is the difference between Cloud Gpu vs Data Scientist?

AspectCloud GpuData Scientist
Required CredentialsKnowledge of cloud platforms, GPU computing, and basic programmingDegree in data science, statistics, or related field; often Python or R skills
Work EnvironmentCloud-based infrastructure, hardware management, and GPU resourcesData analysis, modeling, and visualization in office or remote settings
Industry UsageTech, AI, machine learning, and high-performance computingBusiness, finance, healthcare, and research sectors

While Cloud Gpu specialists focus on managing GPU resources in cloud environments for high-performance tasks, Data Scientists analyze data to extract insights and build models. Both roles often collaborate in AI projects but differ in technical focus and daily tasks.

What other helpful pages are available for Cloud Gpu?

Other pages related to Cloud Gpu:

Infographic showing various Cloud Gpu job openings in the United States as of September 2026, with employment types broken down into 92% Full Time, 3% Part Time, and 5% Contract. Highlights an 76% Physical, 6% Hybrid, and 18% Remote job distribution, with an average salary of $128,365 per year, or $61.7 per hour.

GPU Solutions Engineer

Remote

Vultr
Software Development • 51 - 200 employees
Learn more about Vultrexternal

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 19 days ago

Job description

Who We Are
Vultr is on a mission to make high-performance cloud infrastructure easy to use, affordable, and locally accessible for enterprises and AI innovators around the world. With 33 global cloud data center locations, Vultr is trusted by hundreds of thousands of active customers across 185 countries for its flexible, scalable, global Cloud Compute, Cloud GPU, Bare Metal, and Cloud Storage solutions. In December 2024 Vultr announced an equity financing at a $3.5 billion valuation. Founded by David Aninowsky and self-funded for over a decade, Vultr has grown to become the world's largest privately-held cloud infrastructure company.
Vultr Cares
  • 100% company-paid insurance premiums for employee medical, dental and vision plans.
  • 401(k) plan that matches 100% up to 4%, with immediate vesting
  • Professional Development Reimbursement of $2,500 each year
  • 11 Holidays + Paid Time Off Accrual + Rollover Plan
  • Commitment matters to Vultr! Increased PTO at 3 year and 10 year anniversary + 1 month paid sabbatical every 5 years + Anniversary Bonus each year
  • $500 stipend for remote office setup in first year + $400 each following year
  • Internet reimbursement up to $75 per month
  • Gym membership reimbursement up to $50 per month
  • Company paid Wellable subscription
Join Vultr
Vultr is seeking a highly skilled and experienced GPU Solutions Engineer to lead customers designing, implementing, and optimizing solutions on Vultr's GPU platform. This role partners closely with Direct Sales, Customer Success, Product Management, Engineering and Support Departments to bring AI, ML, GPU workloads to life. The ideal candidate is technically strong and highly collaborative. You have significant hands on experience in cloud infrastructure, networking, Kubernetes and modern GPU computing architectures. You are comfortable translating complex technical concepts into clear solutions, solving real-world challenges, guiding customers from initial design into production and collaborating internally and externally. This is a highly visible role in a high-growth technology company, which will require strong problem-solving skills, customer engagement, and the ability to operate independently in a fast-paced environment. You will directly influence customer adoption and the overall experience on Vultr's platform. This is your opportunity to join our fast growing team and leave your mark on Vultr and the future of Cloud Infrastructure.
Key Responsibilities
  • Engage collaboratively with customers to understand their objectives.
  • Create innovative Solutions and Architectures to solve complex Customer use cases.
  • Establish relationships within Customers independent of Account Executives.
  • Educate customers on the value that Vultr provides and expand their horizons about the art of the possible.
  • Participate in deep architectural discussions and design exercises to create world-class solutions at Vultr.
  • Collaborate with Engineering and Product Management to deliver Voice of the Customer to guide Product and Feature development.
  • Lead resolution of complex customer challenges.
  • Partner with Marketing to create reference architectures, white papers, workshops, and demonstrations for internal and external uses.
  • Travel 25%

Qualifications
  • Highly motivated / self-starter with a sense of ownership, willingness to learn, and desire to succeed.
  • A collegial and collaborative approach working across Departments and Seniority levels within Vultr's Customers and Vultr.
  • Skilled at influencing, guiding, and facilitating stakeholders and peers with decision making.
  • Ability to articulate technical and business concepts to diverse stakeholders.
  • Demonstrated willingness and ability to dig into unfamiliar territories to solve complex challenges.
  • Experience with structured sales engagement models MEDDPIC, Sandler, BANT, etc.
  • Expertise in the GPU ecosystem from GPU Hardware, Bare Metal and Virtualized Cloud Delivery, AL & ML frameworks and AI & ML Ops orchestration.
  • Extensive knowledge of AI Models / Algorithms, Libraries, Compilers and Runtimes for diverse silicon ecosystems.
  • GPU benchmarking and workload testing experience.
  • Demonstrated experience with workload orchestration, Kubernetes and Slurm.
  • System and Cluster level understanding of x86 server hardware architecture and Linux OS.
  • Hands on with Infrastructure as Code methodologies including, Terraform, Ansible, etc.
  • Networking experience, including knowledge of Infiniband, RoCE / UEC Ethernet, or other networking protocols.
  • NCCL / RCCL performance optimization.
  • High Performance Storage experience, knowledge of performant multi-user offerings including Open Source and COTS options.
  • 5+ years of design, implementation, or consulting in applications and infrastructure experience
  • 4+ years of Solution Engineering, Sales Engineering, Professional Services or Consulting experience
  • 3+ year of experience deploying GPU-based AI, ML & Analytics solutions (e.g., for Training, Inference, Fine Tuning, Reinforcement Learning, Agentic Harnesses)

Compensation
$180,000 - $200,000
Final compensation will vary depending on years of experience, background/skill set, location, and applicable laws.
Inclusion & Privacy
We are an equal opportunity employer and are committed to creating an inclusive environment for all employees. We welcome applications from individuals of all backgrounds and experiences, and we prohibit discrimination based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status under applicable laws. Vultr will consider qualified applicants with arrest or conviction records in accordance with applicable laws and will not conduct a background check until after an offer of employment has been extended and accepted.
We also take your privacy seriously. We handle personal information responsibly and follow applicable laws, including U.S. privacy rules and India's Digital Personal Data Protection Act, 2023. Your data is used only for legitimate business purposes and is protected with proper security measures.
Where allowed by law, applicants may request details about the data we collect, access or delete their information, withdraw consent for its use, and opt out of nonessential communications. For more details, please see our Privacy Policy.

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