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Remote Gpu Programming Jobs in Durham, NC (NOW HIRING)

Berriehill Research

Senior AI Systems Engineer

Raleigh, NC · On-site +1

$92K - $126K/yr

Experience with GPU-based systems or running AI models in HPC environments. * Experience writing ... This position may be performed fully remote, hybrid, or onsite at an ARA office. Preference will be ...

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Remote Gpu Programming information

See Durham, NC salary details

$31.9K

$62.8K

$92.3K

How much do remote gpu programming jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote gpu programming in Durham, NC is $62,785.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,800.00 and $77,300.00 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 are popular job titles related to Remote Gpu Programming jobs in Durham, NC?

For Remote Gpu Programming jobs in Durham, NC, the most frequently searched job titles are:

What job categories do people searching Remote Gpu Programming jobs in Durham, NC look for?

The top searched job categories for Remote Gpu Programming jobs in Durham, NC are:

What cities near Durham, NC are hiring for Remote Gpu Programming jobs?

Cities near Durham, NC with the most Remote Gpu Programming job openings:

Remote Gpu Programming jobs near you
Infographic showing various Remote Gpu Programming job openings in Durham, NC 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 $62,785 per year, or $30.2 per hour.

Senior AI Systems Engineer

Berriehill Research

Raleigh, NC • On-site, Remote

$92K - $126K/yr

Full-time

Re-posted 19 days ago

Job description

Essential Functions:

  • Lead the deployment, integration, and operational support of AI platforms, tools, and services, ensuring compatibility with existing systems and enterprise processes.
  • Design, implement, monitor, and optimize AI infrastructure, working with server, cloud, and platform engineering teams.
  • Operationalize machine learning workflows and support AI-enabled applications from development through production deployment and sustainment.
  • Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and lifecycle management.
  • Implement infrastructure automation using scripting, Infrastructure as Code, and configuration management practices.
  • Provide ongoing technical support, troubleshooting, root cause analysis, and documentation for AI platforms and user-facing AI services.
  • Maintain observability across AI systems through logging, metrics, performance monitoring, alerting, and incident response practices.
  • Ensure security, compliance, and governance requirements are met, including participation in audits, vulnerability management, and secure architecture reviews.
  • Assess and implement system enhancements to improve performance, scalability, reliability, and cost efficiency.
  • Collaborate across divisions to support diverse AI initiatives and align technical implementations with mission and business objectives.
  • Evaluate emerging AI tools, frameworks, and infrastructure approaches for operational fit, supportability, and long-term value.
  • Develop and maintain technical documentation, runbooks, architecture diagrams, and operational procedures.

Experience and Skills Required:

  • Bachelor’s degree in computer science, Engineering, Information Technology, or a related STEM field with 8-10 years of engineering experience. 
  • 2+ years of experience supporting AI/ML platforms, MLOps workflows, model deployment, or AI-enabled infrastructure.
  • Strong coding and automation skills in Python, Bash, or similar scripting languages.
  • Experience with AI/ML frameworks and tooling such as PyTorch, Hugging Face, or similar ecosystems.
  • Proficiency with DevOps and MLOps practices, including CI/CD pipelines, Git-based workflows, containerization, and Kubernetes.
  • Experience deploying AI/ML models or AI services into operational environments, including containerized, cloud, or high-performance computing environments.
  • Familiarity with security frameworks and compliance standards such as NIST and CMMC.
  • Familiarity with AI security functionality in enterprise environments including OAuth
  • Strong communication skills and the ability to collaborate effectively across technical and non-technical teams.

Preferred:

  • Advanced degree or certifications related to AI or machine learning.
  • Experience integrating AI models into scientific workflows.
  • Familiarity with large language model (LLM) APIs and orchestration frameworks such as OpenAI, Hugging Face, LangGraph, or LangChain.
  • Experience with model serving, inference optimization, or AI platform tools such as MLflow, Kubeflow, vLLM, or similar.
  • Experience with simulations for scientific or engineering projects, particularly physical systems simulations.
  • Experience with GPU-based systems or running AI models in HPC environments.
  • Experience writing and deploying MCP Servers on Kubernetes
  • DoD experience
  • Secret Security Clearance – Active or Inactive

Education:

  • Bachelor’s degree in CS, Software Engineering or other IT-related field or equivalent experience

REMOTE WORK NOTICE: This position may be performed fully remote, hybrid, or onsite at an ARA office. Preference will be given to candidates located onsite in the Albuquerque, NM and Raleigh, NC area.

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