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Remote Gpu Programming Jobs in Pittsburgh, PA (NOW HIRING)

Familiarity with GPU-accelerated systems and AI infrastructure requirements * Experience with ... However, we are open to remote candidates who meet the qualifications and can work effectively from ...

Familiarity with GPU-accelerated systems and AI infrastructure requirements * Experience with ... However, we are open to remote candidates who meet the qualifications and can work effectively from ...

SVP, Sales

Pittsburgh, PA · Remote

$220K - $320K/yr

... forefront of enterprise GPU compute. * Build and shape a high-performing enterprise sales ... Remote nationwide. Travel to data center partner sites, customer meetings, conferences, and ...

New

SVP, Sales

Pittsburgh, PA · Remote

$220K - $320K/yr

... forefront of enterprise GPU compute. * Build and shape a high-performing enterprise sales ... Remote nationwide. Travel to data center partner sites, customer meetings, conferences, and ...

New

Remote Gpu Programming information

See Pittsburgh, PA salary details

$32K

$63.1K

$92.7K

How much do remote gpu programming jobs pay per year?

As of Aug 22, 2026, the average yearly pay for remote gpu programming in Pittsburgh, PA is $63,078.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $77,700.00 per year, depending on experience, location, and employer.

What is remote GPU programming?

Remote GPU programming refers to the practice of developing and running code that utilizes graphics processing units (GPUs) on computers or servers that are accessed over a network, rather than on your local machine. This approach allows developers to leverage powerful, often cloud-based, GPU resources to handle computationally intensive tasks like machine learning, scientific simulations, or rendering without needing specialized hardware themselves. It often involves using remote desktop tools, cloud platforms, or custom APIs to access and manage GPU resources remotely.

What are the key skills and qualifications needed to thrive as a remote GPU programmer?

To thrive as a Remote GPU Programmer, you need in-depth knowledge of parallel computing, proficiency in programming languages like C/C++, and experience with GPU architectures, often backed by a degree in computer science or a related field. Familiarity with technical tools such as CUDA, OpenCL, and GPU profiling/debugging systems is commonly required, along with certifications in GPU programming or high-performance computing. Strong problem-solving abilities, self-motivation, and effective remote communication skills help individuals excel in distributed teams. These competencies are crucial for efficiently developing and optimizing GPU-accelerated applications while collaborating across remote environments.

What are some common challenges faced by professionals in remote GPU programming roles, and how can they be addressed?

Remote GPU programming roles often involve unique challenges such as managing high-latency connections to remote servers, troubleshooting hardware-specific issues without physical access, and ensuring code compatibility across different GPU architectures. Effective communication with distributed teams is crucial, as is using robust remote debugging tools and version control systems. Staying proactive with documentation and regularly syncing with team members can help address these obstacles and support successful project delivery.

What job categories do people searching Remote Gpu Programming jobs in Pittsburgh, PA look for?

The top searched job categories for Remote Gpu Programming jobs in Pittsburgh, PA are:

What cities near Pittsburgh, PA are hiring for Remote Gpu Programming jobs?

Cities near Pittsburgh, PA with the most Remote Gpu Programming job openings:

Infographic showing various Remote Gpu Programming job openings in Pittsburgh, PA as of August 2026, with employment types broken down into 70% Full Time, and 30% Contract. Highlights an 100% Remote job distribution, with an average salary of $63,078 per year, or $30.3 per hour.

Lead GPU Cluster Solutions Architect

Orion Placement

Pittsburgh, PA • Remote

$140K - $240K/yr

Full-time

Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Job description

Pay: $140,000.00 - $240,000.00 per year

Why This Is a Great Opportunity

  • Own the technical architecture behind next-generation GPU and AI compute deployments.
  • Design sophisticated GPU clusters from client requirements through production-ready architecture.
  • Work directly with NVIDIA Reference Architecture, high-speed networking, storage, connectivity, and availability strategy.
  • Solve challenging infrastructure problems where performance, reliability, power, cooling, and hardware constraints all matter.
  • Have significant technical ownership over designs supporting enterprise and neocloud deployments.
  • Collaborate closely with deployment, data center, supply chain, and program leadership to turn architecture into real-world infrastructure.
  • Join a fast-growing AI infrastructure environment where your technical decisions directly impact customer outcomes.
  • Competitive bonus and equity opportunity in addition to base compensation.

Location: Remote nationwide, with preference for candidates based in the US. Travel to data center partner sites is required.

Note: Must have 7+ years of directly relevant experience in solutions architecture, network engineering, or systems engineering supporting GPU, HPC, or large-scale compute infrastructure. Candidates must have hands-on GPU cluster design experience plus strong InfiniBand, RoCE, or high-speed Ethernet networking expertise. Generic cloud architecture or enterprise networking experience without meaningful GPU/HPC infrastructure exposure will not meet the requirements.

About Us

We are building next-generation AI infrastructure that gives enterprises access to high-performance GPU compute with speed, flexibility, and reliability. Our technical teams design and deploy sophisticated GPU clusters across data center environments, and we are looking for an architect who can turn demanding customer requirements into robust, buildable infrastructure. Confidential Employer.

Job Description

  • Own end-to-end technical architecture for GPU cluster deployments from customer requirements through deployment-ready design.
  • Design GPU cluster configurations spanning compute, storage, networking, software requirements, and supporting infrastructure.
  • Translate client technical requirements into complete bills of design covering all required compute, storage, networking, and connectivity components.
  • Apply NVIDIA Reference Architecture principles, including HGX and NVL72-based GPU cluster designs.
  • Design high-performance network fabrics using InfiniBand, RoCE, and high-speed Ethernet based on workload and performance requirements.
  • Incorporate internet, VPN, firewall, dedicated circuit, protected optical, and other connectivity requirements into cluster architectures.
  • Develop hot and cold sparing strategies designed to meet contracted availability and SLA commitments.
  • Adapt cluster designs to site-specific power, cooling, space, hardware, and deployment constraints.
  • Partner with data center teams to account for real-world facility limitations when finalizing technical architecture.
  • Work with Supply Chain to ensure architecture decisions align with realistic hardware availability and lead times.
  • Partner with deployment leadership and program management to translate designs into executable build plans.
  • Support acceptance test planning and define technical criteria that validate the deployed architecture against the approved design.
  • Evaluate and incorporate high-speed shared storage solutions such as Weka, VAST Data, and DDN where appropriate.
  • Maintain technical ownership of architecture decisions while balancing performance, availability, cost, schedule, and operational supportability.

Qualifications

  • 7+ years of experience in solutions architecture, network engineering, systems engineering, or similar roles supporting GPU, HPC, or large-scale compute infrastructure.
  • Deep working knowledge of NVIDIA Reference Architecture and GPU cluster design principles.
  • Hands-on experience designing InfiniBand, RoCE, and/or high-speed Ethernet fabrics.
  • Proven experience designing GPU or HPC clusters rather than solely consuming cloud infrastructure.
  • Experience developing sparing and spares strategies for mission-critical infrastructure.
  • Experience integrating firewalls, VPNs, dedicated circuits, protected optical connectivity, and related networking requirements into infrastructure designs.
  • Experience with high-speed shared storage technologies such as Weka, VAST Data, or DDN.
  • Strong understanding of compute, storage, networking, and data center infrastructure dependencies.
  • Ability to translate complex customer requirements into complete, practical, buildable technical architectures.
  • Strong cross-functional communication and documentation skills.
  • Experience supporting enterprise customers or neocloud deployments is preferred.
  • NVIDIA NCP program or certification experience is a plus.
  • Experience with capacity planning or sparing modeling tools is a plus.

Why You Will Love Working Here

  • Work on technically challenging GPU infrastructure projects at the center of the AI compute market.
  • Own architecture decisions that directly influence performance, reliability, scalability, and customer success.
  • Gain exposure to cutting-edge NVIDIA GPU architectures and high-speed networking technologies.
  • Collaborate with experienced infrastructure, deployment, data center, supply chain, and executive teams.
  • Work remotely while remaining closely connected to real-world data center deployments.
  • Opportunity to help establish repeatable architecture standards as the business scales.
  • Competitive base compensation plus bonus and equity.
  • Make a visible impact in a high-growth environment where strong technical judgment is valued.

JPC-1766

Benefits:

  • Dental insurance
  • Life insurance
  • Paid time off
  • Retirement plan
  • Vision insurance