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Remote Gpu Engineer Jobs in Rutherford, NJ (NOW HIRING)

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 ...

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 ...

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David Joseph & Company

AI Field Engineer

New York, NY · On-site +1

$176K - $228K/yr

Experience with inference serving frameworks (vLLM, SGLang, TensorRT-LLM) and cloud GPU ... New York, NY or San Mateo, CA; open to remote within the US. * Regular on-site customer travel ...

vCluster Labs

Sr. Solutions Engineer

New York, NY · Remote

$140K - $180K/yr

As a Senior Solutions Engineer at vCluster, you aren't just giving product demos; you are the ... and we have a remote-first work culture. We are the leading platform for operating GPU ...

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Mercor

MLOps Engineer - AI Specialist

New York, NY · Remote

$90 - $140/hr

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to ... Experience writing or optimizing custom GPU kernels using Pallas (JAX) or Triton . * Demonstrable ...

Lightning AI

Infrastructure Engineer (Storage)

New York, NY · On-site +1

$117K - $154K/yr

This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote ... Experience supporting GPU-based workloads or large-scale compute clusters Compensation We are ...

Mercor

PyTorch MLOps Engineer - AI Specialist

New York, NY · Remote

$70 - $110/hr

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to ... Experience writing or optimizing custom GPU kernels using Triton or Pallas . * Demonstrable career ...

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Remote Gpu Engineer information

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How much do remote gpu engineer jobs pay per hour?

As of Jul 2, 2026, the average hourly pay for remote gpu engineer in Rutherford, NJ is $54.67, according to ZipRecruiter salary data. Most workers in this role earn between $44.09 and $63.46 per hour, depending on experience, location, and employer.

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.

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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Remote Gpu Engineer jobs near you
Infrastructure Engineer (GPU & Compute)

Infrastructure Engineer (GPU & Compute)

Lightning AI

New York, NY • On-site, Remote

$117K - $154K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 20 hours ago

Job description

Who We Are
Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems-designed to take ideas from research to production with less friction.
Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.
We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.
What We're Looking For
Lightning AI is seeking a GPU & Compute Infrastructure Engineer to join our Infrastructure Engineering team.
In this role, you will own image management, system diagnostics, and validation across large-scale bare-metal compute infrastructure, with a particular focus on GPU-enabled systems. You will work at the intersection of hardware, systems, and software-developing automation, improving reliability, and enabling efficient cluster bring-up for AI/ML and HPC workloads.
You will play a key role in owning and evolving our image pipeline, running validation environments and test clusters, and supporting both system-level and GPU hardware qualification. This role is critical to ensuring that our infrastructure is consistent, performant, and ready to support demanding AI workloads from day one.
We're flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.
What You'll Do
Systems, Image & Validation Infrastructure
  • Own and evolve systems for image management, deployment, and validation across bare-metal infrastructure
  • Run and maintain test clusters used for system validation, diagnostics, and bring-up
  • Validate firmware, drivers, and OS images across compute and GPU-enabled systems
  • Support hardware qualification efforts for next-generation platforms
GPU Diagnostics & Performance
  • Own GPU diagnostics and validation workflows across large-scale infrastructure
  • Diagnose and resolve complex issues across GPUs, drivers, OS, and hardware layers
  • Analyze system and GPU performance using tools such as NVIDIA DCGM
  • Identify failure patterns and drive improvements in system stability and validation coverage
Automation & Tooling
  • Build and maintain automation for provisioning, validation, and system bring-up
  • Develop Python-based tools and workflows to improve efficiency and reduce manual operational overhead
  • Improve the reliability, repeatability, and scalability of image pipelines and validation systems
Systems & Operations
  • Manage and operate Linux-based systems in production and validation environments
  • Manage virtualization technology
  • Support bare-metal provisioning workflows, including PXE and image-based systems
  • Interface with hardware management systems (e.g., IPMI, Redfish) for monitoring and debugging
Cross-Functional Collaboration
  • Partner with Infrastructure, Hardware, and Data Center teams on system bring-up and validation
  • Collaborate with platform and ML teams to ensure systems meet workload requirements
  • Contribute to best practices for provisioning, diagnostics, and lifecycle management of infrastructure
What You'll Need
Required Qualifications
  • 5+ years of experience in infrastructure engineering, systems engineering, or related roles
  • Strong Linux systems experience in production environments
  • Hands-on experience with GPU-enabled systems and tools such as NVIDIA DCGM
  • Familiarity with bare-metal provisioning and system bring-up workflows
  • Proficiency in Python or similar scripting/programming languages for automation
  • Ability to debug complex issues across hardware, OS, GPUs, and system software
Ideal Experience
  • Experience with high-performance interconnects (e.g., InfiniBand, NVLink)
  • Experience with PXE boot environments, LiveCD systems, or image-based provisioning workflows
  • Experience with hardware management interfaces such as iDRAC, IPMI, or Redfish
  • Data center operations experience, including working with physical hardware
  • Experience supporting AI/ML or HPC workloads at scale
  • Experience with GPU validation frameworks or large-scale hardware qualification processes

Compensation
We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits.
The anticipated annual base salary range for this role is:
$180,000-$200,000 USD
Benefits and Perks
We offer a comprehensive and competitive benefits package designed to support our employees' health, well-being, and long-term success. Benefits may vary by location, team, and role.
Benefits include:
  • Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
  • Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
  • Generous paid time off, plus holidays
  • Paid parental leave
  • Professional development support
  • Wellness and work-from-home stipends
  • Flexible work environment

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

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