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Remote Gpu Engineer Jobs (NOW HIRING)

iXsystems

Software Engineer III (AI)

Campbell, CA · On-site +1

$140K - $160K/yr

This is a remote position in the United States Base Pay Range The base pay range of this position ... GPU-accelerated inference. Build out the inference path using cuVS/CAGRA and similar libraries ...

TrueNAS

Software Engineer III (AI)

Campbell, CA · Remote

This is a remote position in the United States Base Pay Range The base pay range of this position ... GPU-accelerated inference. Build out the inference path using cuVS/CAGRA and similar libraries ...

PICTOR LABS INC

$89K - $123K/yr

Remote US Company: Pictor Labs Employment Type: Full-time Responsibilities * Design, development ... GPU utilization and throughput * Profile and optimize deep neural networks on NVIDIA GPUs using ...

STN Inc

Site Reliability Engineer

San Francisco, CA · Remote

$67.25 - $89.25/hr

Remote (US) Department: Cloud Platform Engineering / SRE/Reliability Position summary The Site Reliability Engineer (SRE) owns reliability, observability, and incident response for the GPU One ...

Vultr

Staff AI/ML Infrastructure Engineer

$145K - $160K/yr

... 500 stipend for remote office setup in first year + $400 each following year * Internet ... Design and maintain GPU and bare metal infrastructure in containerized and physical environments

vCluster Labs

AI Infrastructure Engineer

New York, NY · Remote

$150K - $200K/yr

As an AI Infrastructure Engineer, your role will include: * Lead Technical Deployments: Drive end ... and we have a remote-first work culture. We are the leading platform for operating GPU ...

PsiQuantum

Senior Software Platform Engineer

$125K - $165K/yr

Remote PsiQuantum's mission is to build the first useful quantum computers--machines capable of ... Make GPU clusters and other infrastructure invisible to the researchers running it. * Own CUDA ...

Biohub

Staff HPC Engineer

San Francisco, CA · On-site +1

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 ...

PRAGMATIKE

CUDA Kernel Engineer

New York, NY · Remote

Remote US Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on ... Profile GPU workloads using tools such as N sight Compute, Nsight Systems, nvprof, and ...

PRAGMATIKE

CUDA Kernel Engineer

Cambridge, MA · Remote

Remote US Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on ... Profile GPU workloads using tools such as N sight Compute, Nsight Systems, nvprof, and ...

PRAGMATIKE

CUDA Kernel Engineer

San Francisco, CA · Remote

Remote US Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on ... Profile GPU workloads using tools such as N sight Compute, Nsight Systems, nvprof, and ...

Runpod, Inc.

Manager, HPC Storage Engineer

Founded in 2022, we are a rapidly growing, well-funded, remote-first company with a global team ... Partner with Datacenter Networking, GPU Platform, SRE, and Product teams to ensure storage systems ...

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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.
Sr. Embedded & Compute Software Developer

Sr. Embedded & Compute Software Developer

Lynx Software Technologies

Remote

$130K - $160K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago

Key responsibilities

  • Design and implement GPGPU and AI inference libraries on top of Vulkan SC drivers, focusing on correctness and performance.

  • Lead porting and release efforts to new platforms and customers, including post-delivery support.

  • Maintain AI model testing infrastructure and define certification requirements for compute libraries.

Job description

Job Title: Sr. Embedded & Compute Software Developer
Location: Remote - US or Canada
Compensation:
US: $130,000 - $160,000 USD + Bonus Eligible
Canada: $110,000 - $140,000 CAD + Bonus Eligible
This role is open to candidates based in the US or Canada. Compensation is location-based and will vary depending on experience, skills, and local market conditions.
Who we are: Lynx delivers modular, open standards-based software that transforms how high-assurance, mission-critical edge systems are built, deployed, and maintained. Our secure edge computing solutions enable innovation and operational excellence in the world's most demanding environments, from aerospace and defense to commercial and industrial systems. We partner across industries including automotive, medical, and critical infrastructure to deliver tailored solutions aligned with each customer's mission and operational requirements. Our key products and services are:
  • MOSA.ic: LYNX MOSA.ic™ is a modular software framework and architecture purpose-built for mission-critical edge computing. Based on the Modular Open Systems Approach (MOSA), it provides a flexible foundation for building secure, scalable, and certifiable edge systems.
  • LYNX MOSA.ic.AI: LYNX MOSA.ic.AI is a unified CPU and GPU software platform that enables deterministic, certifiable deployment of AI and advanced workloads in mission-critical edge systems. It brings control, performance, and lifecycle governance together, allowing AI to operate predictably within safety-critical environments without compromising certification or system integrity.
  • CoreSuite 2.0: CoreSuite 2.0 is Lynx's safety-critical GPU for graphics enablement framework designed for mission-critical edge computing systems. It provides hardware-accelerated graphics, visualization, and video processing capabilities that can be certified for high-assurance systems.
  • Services: Lynx Services is Lynx's professional services organization that helps customers design, integrate, certify, deploy, and maintain safety- and security-critical systems. It supports industries like aerospace, defense, automotive, and industrial computing through consulting, engineering, integration, and lifecycle support, reducing development risk and accelerating certification in standards-driven, mission-critical environment.

Role Overview
This role provides technical leadership in the design, development, and optimization of high-performance GPGPU and AI inference libraries built on top of Vulkan SC drivers. The position focuses on delivering efficient, scalable compute solutions across embedded GPU platforms, including Arm Mali and Intel architectures, while ensuring robust performance and reliability.
Key responsibilities include driving end-to-end library development, from architecture and implementation to optimization and certification, while maintaining AI model testing infrastructure and defining validation standards. The role also leads platform porting and release efforts for new hardware targets and customer deployments, providing ongoing post-delivery support.
In addition to hands-on engineering, this position plays a critical role in cross-functional collaboration: producing clear technical documentation for diverse stakeholders, contributing to competitive market analysis with product management, and supporting continuous improvement of Vulkan SC drivers through debugging and issue resolution.
The role also emphasizes team growth and innovation, including mentoring engineers, onboarding new team members, and exploring emerging AI compute capabilities and use cases to expand the impact of the software stack.
Key Responsibilities
  • Design and implement GPGPU and AI inference libraries on top of our Vulkan SC drivers, with a focus on correctness and performance
  • Optimize AI inference across the embedded GPU platforms we support
  • Lead porting and release efforts to new platforms and customers, including post-delivery support
  • Maintain AI model testing infrastructure and define certification requirements for compute libraries
  • Explore and demonstrate new capabilities and use cases for the compute library portfolio
  • Partner with product management on competitive analysis of AI software offerings
  • Produce documentation that enables knowledge transfer to customers, product management, marketing, and engineering leadership
  • Onboard and mentor new team members
  • Collaborate with Product Management, Product Architecture, and Product Development teams to translate Product Level Requirements into architectural-level decisions.

Qualifications Required
• Bachelor's degree in engineering (Computer, Software, Electrical), Computer Science or related field
• 5+ years of experience in C/C++ software development
• Experience with developing, debugging, and troubleshooting embedded software development
• Experience with ML frameworks such as PyTorch, ONNX, TensorFlow
Preferred:
• Experience with GPU programming APIs: Vulkan, OpenGL, OpenCL, CUDA
• Experience with embedded real-time safety-critical operating systems (preferably Lynx, Deos, VxWorks)
• Experience with DO-178 or ISO26262 software development processes
Sound Exciting? Get in touch today! We have very robust benefits including:
  • Low-cost Medical / Dental / Vision coverage options
  • 401K with generous employer match
  • Responsible Paid Time Off + Paid Holidays
  • Remote work opportunities based on role
  • Employee Assistance Program (EAP)
  • Career growth and professional development opportunities

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

Apply