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

Compute Engineer, Deployment

New York, NY · On-site +1

$164K - $206K/yr

You've brought up server or GPU fleets at scale, hundreds of nodes or more, and taken them all the ... acting as remote hands or directing them. * You triage failures methodically across hardware ...

Senior AI Researcher

New York, NY · On-site +1

$150K - $220K/yr

You will collaborate closely with the VP of AI Engineering, the CEO, and a small AI engineering ... New York preference but open to remote; you must work EST hours. Here's How You'll Make an Impact ...

Cloud Architect

New York, NY · Remote

$66.50 - $84.75/hr

... engineering skills and hands-on experience supporting, configuring, and optimizing AI models and ... FULLY REMOTE, INTERVIEW VIA TEAMS A Cloud Architect with AI experience will provide the following ...

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Remote Gpu Engineer information

See Rutherford, NJ salary details

$25

$54

$78

How much do remote gpu engineer jobs pay per hour?

As of Aug 18, 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 is a remote GPU engineer?

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 the key skills and qualifications needed to thrive as a remote GPU engineer?

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 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.

What job categories do people searching Remote Gpu Engineer jobs in Rutherford, NJ look for?

The top searched job categories for Remote Gpu Engineer jobs in Rutherford, NJ are:

What cities near Rutherford, NJ are hiring for Remote Gpu Engineer jobs?

Cities near Rutherford, NJ with the most Remote Gpu Engineer job openings:

Compute Engineer, Deployment

Fluidstack

New York, NY • On-site, Remote

$164K - $206K/yr

Full-time

Re-posted 10 days ago


Job description

About Fluidstack
We exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had to do. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it.
We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI.
We hire people who care deeply about this problem space. If that is you, please apply!
How We Operate
  • Extreme ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done.
  • Velocity. We drive everything forward as fast as possible.
  • First principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.
  • Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.
The Infrastructure Team
Examples of key problems the team is working on
  • Bring gigawatts of accelerators from first power-on to production. Facility availability to ready-for-service across thousands of racks per site, with a new data hall landing every few weeks.
  • Make rack qualification faster than the fleet grows. Firmware baselines, burn-in, and cluster validation proven on every rack before a customer workload touches it, at a pace that never becomes the critical path.
  • Scale by tooling, not headcount. Deployed megawatts grow severalfold next year while the team stays near-flat, because anything done twice by hand becomes software.
Role Scope
  • Own compute turn-up from facility availability to ready-for-service: the stretch after the network hands off and before customers run workloads.
  • Qualify racks at scale: establish firmware baselines, configure BMC and BIOS, run burn-in, and validate at node and cluster level across hundreds of racks per site on GPU and custom accelerator platforms.
  • Drive qualification through the base-management Kubernetes platform and provisioning stack (discovery, imaging, firmware updates, shared services), burning down qual queues with tooling rather than manual runs.
  • Triage hardware failures found in qualification: isolate to component, drive RMA and vendor escalation, and feed failure patterns back into the qual gates.
  • Run turn-up remotely by default, with on-site pulses of roughly a week per data hall as new halls reach facility availability, plus occasional overlapping-site weeks.
  • Partner with network deployment, ICT, data center operations, and hardware teams during turn-up windows, and support incident response on freshly-live capacity.
  • Ability to travel 20-30% of the time to our Data Centers and Labs, as needed.
What We're Looking For
The below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly, tell us where you would.
  • You've brought up server or GPU fleets at scale, hundreds of nodes or more, and taken them all the way to production.
  • You work deep in Linux and out-of-band management: BMC, IPMI, and Redfish are daily tools for you, not occasional lookups.
  • You've automated hardware workflows in Python or Go rather than clicking through them, and the second time you do anything by hand you turn it into software.
  • You've worked physically in data halls, racking, cabling, and swapping components, and you're just as effective acting as remote hands or directing them.
  • You triage failures methodically across hardware, firmware, and software, isolating the fault to a component before reaching for a fix.
  • You travel for turn-up windows when a new data hall comes online.
  • Bonus: Kubernetes-based bare-metal provisioning. Accelerator platform bringup (NVIDIA, AMD, or custom). Burn-in and stress harness design. DCIM and inventory tooling.

We are committed to pay equity and transparency.
Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans' status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email careers@fluidstack.io with your resume/CV, the role you've applied for, and the date you submitted your application-- someone from our recruiting team will be in touch.