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Remote High Performance Computing Jobs in North Carolina

Berriehill Research

Senior AI Systems Engineer

Raleigh, NC · On-site +1

$92K - $126K/yr

... high-performance computing environments. * Familiarity with security frameworks and compliance ... This position may be performed fully remote, hybrid, or onsite at an ARA office. Preference will be ...

VAST Data

Customer Support Engineer

Raleigh, NC · On-site +1

... high-performance computing at customer sites and in the lab. You will work directly with customers, and various business functions: consulting pre-sales teams on technical sales activities ...

VAST Data

Customer Support Engineer

Raleigh, NC · On-site +1

... high-performance computing at customer sites and in the lab. You will work directly with customers, and various business functions: consulting pre-sales teams on technical sales activities ...

NinjaOne

Location - We are flexible on remote working from home, if you are located in the USA and reside in ... Deep expertise with distributed computing systems and container native environments. * Proficient ...

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Remote High Performance Computing information

What is the difference between Remote High Performance Computing vs Remote Data Scientist?

AspectRemote High Performance ComputingRemote Data Scientist
Required CredentialsAdvanced degrees in Computer Science, Engineering, or related fields; experience with HPC systemsDegree in Data Science, Statistics, Computer Science, or related fields; proficiency in programming languages
Work EnvironmentAccess to supercomputers, clusters, or cloud HPC resources; collaborative teamsData analysis environments, cloud platforms, and programming tools; often collaborative
Industry UsageResearch institutions, scientific computing, engineering simulationsTech companies, finance, healthcare, research

Remote High Performance Computing specialists focus on managing and utilizing supercomputing resources for complex simulations and data processing. Remote Data Scientists analyze large datasets to extract insights. While both roles require programming skills and advanced degrees, HPC roles emphasize system management and computational efficiency, whereas Data Scientists focus on data analysis and modeling.

What are the key skills and qualifications needed to thrive as a Remote High Performance Computing (HPC) Specialist, and why are they important?

To thrive as a Remote High Performance Computing (HPC) Specialist, you need expertise in parallel computing, cluster management, and strong programming skills in languages such as Python, C/C++, or Fortran, often backed by a degree in computer science or a related field. Familiarity with HPC job schedulers (like SLURM or PBS), cloud platforms, and Linux-based systems, as well as relevant certifications, is highly valuable. Strong problem-solving abilities, effective communication, and the capacity to work independently are crucial soft skills in remote environments. These competencies ensure efficient deployment, management, and troubleshooting of complex HPC resources while supporting diverse user needs from a distance.

What is Remote High Performance Computing?

Remote High Performance Computing (HPC) refers to the use of powerful computing resources and clusters that are accessed over the internet or a network, rather than being located locally. This setup allows researchers, engineers, and organizations to perform complex computations, simulations, and data analysis from anywhere, without the need for on-site supercomputers. Remote HPC enables scalability, flexibility, and cost-effectiveness by allowing users to leverage shared resources, often provided by cloud service providers or specialized data centers.

How does a Remote High Performance Computing (HPC) professional typically collaborate with research teams and IT staff?

Remote HPC professionals often work closely with research scientists, data analysts, and IT administrators to ensure computational resources are efficiently allocated and optimized for large-scale projects. Collaboration usually happens through virtual meetings, ticketing systems, and shared documentation platforms, requiring strong communication and problem-solving skills. Daily tasks may involve troubleshooting user issues, managing job scheduling, and maintaining cluster performance, all while coordinating with geographically dispersed teams. This dynamic environment fosters continuous learning and exposure to cutting-edge scientific and technical applications.
What are popular job titles related to Remote High Performance Computing jobs in North Carolina? For Remote High Performance Computing jobs in North Carolina, the most frequently searched job titles are:
What job categories do people searching Remote High Performance Computing jobs in North Carolina look for? The top searched job categories for Remote High Performance Computing jobs in North Carolina are:
What cities in North Carolina are hiring for Remote High Performance Computing jobs? Cities in North Carolina with the most Remote High Performance Computing job openings:
Remote High Performance Computing jobs near you

Senior AI Systems Engineer

Berriehill Research

Raleigh, NC • On-site, Remote

$92K - $126K/yr

Full-time

Re-posted 7 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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