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Remote Gpu Engineer Jobs (NOW HIRING)

Vultr

Strategic Technical Account Manager GPU

$115K - $140K/yr

... remote office setup in first year + $400 each following year Internet reimbursement up to $75 per ... Partner with Support, SRE, Networking, NOC, and Product Management & Engineering to resolve high ...

Nebius

GPU Cluster Architect

$184K - $318K/yr

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we ... Remote work reimbursement: Up to $85/month for mobile and internet. * Disability & life insurance

Runpod, Inc.

Principal Security Engineer

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 ...

Danaher

Senior Software Engineer - USA Remote

Raleigh, NC · Remote

$119K - $157K/yr

This fully remote position is part of the Leica Microsystems Research and Development organization ... GPU programming using CUDA; Targeting ARM & X86 processing environments; User Interface design;

Danaher

Senior Software Engineer - USA Remote

Durham, NC · Remote

$118K - $156K/yr

This fully remote position is part of the Leica Microsystems Research and Development organization ... GPU programming using CUDA; Targeting ARM & X86 processing environments; User Interface design;

Danaher

Senior Software Engineer - USA Remote

$125K - $165K/yr

This fully remote position is part of the Leica Microsystems Research and Development organization ... GPU programming using CUDA; Targeting ARM & X86 processing environments; User Interface design;

H R PUNDITS INC

Senior Graphics Engineer

Phoenix, AZ · Remote

$130K/yr

Remote Rate: $130K per annum Job Responsibilities Develop and optimize features in a modern, low ... improve GPU and CPU performance across the rendering pipeline, including multi-GPU real-time ...

Nvidia

$135K - $181K/yr

We are seeking a Principal Systems Engineer to define the vision and roadmap for memory management ... Deep understanding of memory hierarchies (GPU HBM, host DRAM, SSD, and remote/object storage) and ...

Nebius

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:

Mantari

Software Engineer

Torrance, CA · On-site +1

... 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

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Remote Gpu Engineer information

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How much do remote gpu engineer jobs pay per hour?

As of Jun 29, 2026, the average hourly pay for remote gpu engineer in the United States is $53.63, according to ZipRecruiter salary data. Most workers in this role earn between $43.27 and $62.26 per hour, depending on experience, location, and employer.

What engineer makes $500,000 a year?

A senior GPU engineer or hardware engineer with extensive experience in graphics processing units, often working in leading tech companies or specialized hardware firms, can earn $500,000 or more annually. High compensation typically includes base salary, bonuses, and stock options, especially for those with advanced skills in hardware design, performance optimization, and deep knowledge of GPU architectures.

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.

How can I make 2000 a week working from home?

A remote GPU engineer can earn $2,000 or more weekly by working on high-demand projects such as AI, machine learning, or rendering, often requiring advanced skills in GPU programming, deep learning frameworks, and experience with tools like CUDA or TensorFlow. Achieving this income typically involves freelance contracts, consulting, or full-time roles with competitive pay, and may require specialized certifications or a strong portfolio. Consistent high performance and building a reputation in the industry can help secure higher-paying opportunities.

What engineers make $300,000 a year?

Senior GPU engineers, machine learning engineers, and software engineers with specialized skills in graphics processing, deep learning, or high-performance computing can earn $300,000 or more annually, especially with experience, advanced certifications, and working in high-demand industries like AI, gaming, or data centers. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups.

How can I make $100,000 a year working from home?

A remote GPU engineer can reach a $100,000 annual salary by gaining specialized skills in GPU programming, deep learning, or high-performance computing, and obtaining relevant certifications. Building a strong portfolio, gaining experience with tools like CUDA or TensorFlow, and working for companies that offer remote positions with competitive pay are key factors.

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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What cities are hiring for Remote Gpu Engineer jobs? Cities with the most Remote Gpu Engineer job openings:
What are the most commonly searched types of Gpu Engineer jobs? The most popular types of Gpu Engineer jobs are:
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Remote Gpu Engineer jobs near you
Infographic showing various Remote Gpu Engineer job openings in the United States as of June 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 100% Remote job distribution, with an average salary of $111,552 per year, or $53.6 per hour.
Strategic Technical Account Manager GPU

Strategic Technical Account Manager GPU

Vultr

Remote

$115K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 9 days ago

Key responsibilities

  • Lead onboarding and advise customers on the architecture and deployment of GPU clusters for AI and high-performance workloads.

  • Identify technical bottlenecks and provide recommendations for performance optimization and scaling of GPU workloads.

  • Own the long-term technical strategy, host technical review meetings, and manage incident resolution for assigned GPU/AI accounts.

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
The GPU-focused Technical Account Manager (TAM) leads the post-sales technical success of customers deploying large-scale AI, training, inference, and high-performance GPU workloads on the company's platform. This includes customers using NVIDIA GPU clusters, AMD GPU clusters, GPU VMs, and rack-scale bare-metal environments.
You will act as a trusted advisor across LLM training, fine-tuning, RAG workloads, distributed training frameworks, storage throughput requirements, multi-GPU scaling, and performance tuning. This role requires deep technical fluency and exceptional customer management skills to help AI/ML teams achieve predictable, cost-efficient, high-performance outcomes.
Key Responsibilities
AI/GPU Onboarding & Workload Architecture
  • Lead onboarding for customers deploying GPU clusters (bare metal, VMs, or hybrid).
  • Advise on cluster design: multi-GPU topology, NVLink/NVSwitch considerations, RDMA, Infiniband and RoCE Ethernet, networking throughput, and storage IOPS requirements.
  • Guide customers in selecting GPU types and configurations based on workload (training, fine-tuning, inference, embeddings, RAG pipelines).
  • Support distributed frameworks: PyTorch, TensorFlow, DeepSpeed, Megatron, JAX, Ray, Mosaic, HuggingFace, etc.
  • Advanced hands on Kubernetes skills
  • Advanced hands on SLURM skills

Performance Optimization & Scaling
  • Identify bottlenecks (network, storage, memory bandwidth).
  • Provide tuning recommendations for batch size, mixed precision, parallelization strategies, and checkpointing.
  • Help customers evaluate cost vs. performance tradeoffs (GPU mix, CPU pairing, instance types, cluster sizing).

Technical Relationship Ownership
  • Own the long-term technical strategy across assigned GPU/AI accounts, including hyperscalers, labs, and high-growth AI startups.
  • Host recurring technical review meetings, roadmap reviews, and optimization sessions.
  • Define scaling plans, future GPU reservation needs, and capacity forecasting.
  • Incident & Escalation Management
  • Partner with Support, SRE, Networking, NOC, and Product Management & Engineering to resolve high-urgency incidents.
  • Manage outage communications, corrective action plans, and postmortem reviews with customers.
  • Advocate for GPU reliability improvements and influence roadmap priorities.

Account Growth & Expansion
  • Identify opportunities for expanded clusters, high speed storage, or networking upgrades.
  • Support Sales with technical validation and architecture diagrams needed for expansion.

Customer Advocacy & Product Feedback
  • Provide structured feedback on existing and future GPU offerings, networking fabrics, storage platforms, and upcoming AI/ML platform features.
  • Partner with Product on early access programs (new GPUs, pipelines, orchestration, etc.).

Qualifications
  • 2-5+ years as an AI/ML Engineer, AI/ML Ops, Technical Account Manager, HPC Engineer, Sales/Solutions Engineer or relevant technical role.
  • Strong knowledge of GPU hardware architectures (NVIDIA/AMD), CUDA/ROCm, distributed training, and ML frameworks.
  • Experience with Linux tuning, networking (Infiniband, RoCE fabrics).
  • Experience with high-performance storage systems (DDN, NetApp, Vast, Weka, etc.).
  • Ability to communicate complex concepts clearly to both executives and engineering teams.
  • Prior experience supporting hyperscale, AI labs, or large cluster deployments is a plus.
  • Cloud Native Computing Foundation Certified Kubernetes Administrator (CKA) certification is a plus.

Compensation
$115,000 - $140,000
This salary can vary based on location, years of experience, background and skill set.
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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