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Freelance High Performance Computing Engineer Jobs

Citizenship) KEY SUMMARY We are seeking an innovative and driven HPC (High-Performance Computing) Software Engineer to develop and optimize software solutions for cutting-edge computational ...

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Freelance High Performance Computing Engineer information

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$53.5K

$131.3K

$193.5K

How much do freelance high performance computing engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for freelance high performance computing engineer in the United States is $131,349.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,500.00 and $147,500.00 per year, depending on experience, location, and employer.

How do freelance high performance computing engineers typically collaborate with client teams during projects?

Freelance HPC Engineers often work closely with client engineering, research, or IT teams to design, implement, and optimize computational solutions. Collaboration usually occurs through regular virtual meetings, code reviews, and progress updates to ensure alignment with project goals and technical requirements. Clear communication and documentation are essential, as freelancers may need to integrate their work into larger systems or hand off projects to in-house teams. Building strong relationships and understanding the client's workflow help ensure successful project delivery and can lead to ongoing opportunities.

What is a freelance high performance computing engineer?

A Freelance High Performance Computing (HPC) Engineer is a professional who specializes in designing, implementing, and optimizing computing systems that handle complex, large-scale computations. They work independently or on a contract basis for different organizations, helping to develop and maintain supercomputers, clusters, and parallel processing applications. Their expertise is often sought in fields like scientific research, finance, artificial intelligence, and engineering where processing large datasets quickly is essential. Freelancers in this field typically possess strong programming skills, knowledge of HPC architectures, and experience with performance tuning and troubleshooting.

What are the key skills and qualifications needed to thrive as a freelance high performance computing engineer?

To thrive as a Freelance High Performance Computing Engineer, you need expertise in parallel programming, cluster management, and a strong background in computer science or engineering. Familiarity with tools such as MPI, OpenMP, Linux environments, and cloud-based HPC platforms, along with certifications in cloud services or HPC technologies, is highly beneficial. Excellent problem-solving, project management, and communication skills set top freelancers apart when working with diverse clients. These competencies ensure the delivery of optimized, scalable solutions and effective collaboration in complex technical projects.

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

AspectFreelance High Performance Computing EngineerFreelance Data Scientist
CredentialsAdvanced degrees in computer science, engineering, or related fields; knowledge of HPC systemsDegree in data science, statistics, or related fields; proficiency in programming and analytics
Work EnvironmentSpecialized computing clusters, research labs, or cloud HPC platformsData analysis environments, cloud platforms, and business analytics tools
Industry UsageResearch institutions, scientific computing, engineering simulations
Search & Comparison IntentFocus on high-performance computing tasks, technical skills

While both roles involve advanced technical skills, Freelance High Performance Computing Engineers specialize in optimizing and managing large-scale computing resources for scientific and engineering applications. Freelance Data Scientists focus on analyzing data to extract insights for business or research purposes. The key difference lies in their core focus: HPC engineers work with hardware and system performance, whereas data scientists work with data analysis and modeling.

More about Freelance High Performance Computing Engineer jobs
What cities are hiring for Freelance High Performance Computing Engineer jobs? Cities with the most Freelance High Performance Computing Engineer job openings:
What are the most commonly searched types of High Performance Computing Engineer jobs? The most popular types of High Performance Computing Engineer jobs are:
What states have the most Freelance High Performance Computing Engineer jobs? States with the most job openings for Freelance High Performance Computing Engineer jobs include:
What job categories do people searching Freelance High Performance Computing Engineer jobs look for? The top searched job categories for Freelance High Performance Computing Engineer jobs are:
Infographic showing various Freelance High Performance Computing Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 16% Part Time, 3% Contract, and 1% Nights. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $131,349 per year, or $63.1 per hour.

Research Computing Engineer

Santa Clara University

Santa Clara, CA โ€ข On-site, Remote

$115K - $129K/yr

Full-time

Posted 21 days ago


Job description

Position Title:Research Computing EngineerPosition Type:RegularHiring Range:
$115,200 - $129,600 per year; commensurate with experience
Pay Frequency:Annual

Company Overview:

Santa Clara University is a prestigious academic institution dedicated to advancing research, innovation, and education. We are seeking a visionary and highly skilled Research Computing Engineer to join our dynamic team. This pivotal role will strategically develop and optimize our High-Performance Computing (HPC) infrastructure, directly driving groundbreaking, multi-disciplinary research across the institution.

Job Description:

As the strategic anchor for the SCU High-Performance Computing (HPC) environment, the Research Computing Engineer serves as the primary technical partner between Santa Clara University's research community and its computational infrastructure.

This role focuses on driving the "outer relationship" with users-faculty, researchers, and students-to deeply understand, architect, and translate complex computational workflows into scalable technical solutions. Rather than simply maintaining existing infrastructure, the Research Computing Engineer provides strategic leadership, engineers robust processes, and drives long-term planning to ensure the HPC ecosystem proactively evolves alongside the university's research mission.

The ideal candidate is highly curious, creative, tenacious, and entirely self-directed. They bring an advanced technical toolkit combined with the leadership capacity to identify, define, and resolve complex systemic and human workflows independently and collaboratively.

Work Schedule: This position requires on-site support on a regular basis. On-campus vs. remote schedules will operate on a hybrid model based on strategic and operational tasks.

Essential Duties and Responsibilities

1. Strategic Leadership, Planning, and Research Facilitation

  • Lead the strategic roadmap and long-term capacity planning for SCU's HPC infrastructure, partnering with the Dean and academic stakeholders to forecast future computational demands.

  • Own the full-cycle consultation process with researchers and faculty, translating cutting-edge academic requirements into scalable, robust technical solutions.

  • Architect and implement proactive infrastructure enhancements to optimize application pipelines for emerging domains, including AI, Machine Learning, Data Science, and GPU-accelerated processing.

  • Evaluate, recommend, and drive the adoption of emerging technologies and external integrations with national academic computing resources to expand institutional research capabilities.

  • Provide high-level technical leadership and programming support to resolve complex, multi-disciplinary computational challenges across university departments.

2. Process Innovation, Governance, and Training

  • Design, implement, and institutionalize standard operating procedures (SOPs) and automated workflows for user onboarding, resource allocation, and system governance.

  • Develop lifecycle management processes for scientific software deployment, cluster usage auditing, and data management.

  • Establish system performance metrics and reporting frameworks to showcase HPC utilization and research impacts to executive leadership.

  • Design and spearhead comprehensive training programs, advanced workshops, and modern digital documentation to cultivate a self-sustaining research culture.

  • Lead institutional initiatives to train users in modern code-management, AI-assisted coding, CI/CD, and version control best practices (e.g., Git/GitHub).

3. Full-Cycle HPC Infrastructure Architecture & Operations

  • Own the deployment lifecycle, configuration, and optimization of specialized scientific software, compilers, containerized environments, and shared libraries.

  • Lead the architecture, fine-tuning, and policy creation for workload managers and cluster schedulers (e.g., Slurm) to ensure optimal, equitable resource distribution.

  • Lead the scaling and operational strategy for parallel storage and distributed file systems (e.g., BeeGFS, Lustre), ensuring total data integrity, high-throughput performance, and business continuity.

  • Lead network design and execution within the HPC environment, overseeing high-speed fabrics (e.g., InfiniBand) and complex VLAN configurations.

4. Security Frameworks and Systems Stewardship

  • Architect and enforce comprehensive security frameworks, including server hardening, access controls, and vulnerability mitigation protocols to safeguard sensitive research data.

  • Proactively monitor, analyze, and optimize system telemetry to perform deep root-cause analysis on complex hardware and software bottlenecks.

  • Stay current with emerging trends in HPC, AI, and cloud technologies to inform long-term infrastructure planning.

C. QUALIFICATIONS

1. Knowledge, Skills, and Abilities

  • Full-Cycle Ownership & Strategy: Demonstrated ability to independently design, implement, and govern enterprise-grade computational environments and workflows.

  • Technical Mastery: Advanced, hands-on mastery of Linux systems administration, automated provisioning, and comprehensive package management systems.

  • Scripting and Automation: Demonstrated experience writing and debugging complex scripts in Bash, Python, or Ansible.

  • HPC Ecosystem Expertise: Deep knowledge of workload managers (Slurm), container technologies (Docker, Apptainer), and version control. Proven success implementing distributed file systems (BeeGFS, Lustre) and environment module systems.

  • Cybersecurity Leadership: Advanced understanding of cybersecurity principles, encryption standards, and risk-mitigation strategies unique to open research cluster environments.

  • Communication: Exceptional interpersonal and verbal communication skills; ability to explain complex technical concepts to non-technical users.

  • Problem Solving: Strong analytical skills with a proactive approach to identifying and resolving technical and human issues.

2. Experience and Education

  • Education: Bachelor's degree in Computer Science, Engineering, or a highly quantitative field required. Advanced degree (MS or PhD) strongly preferred to bridge the gap during high-level research consultations.

  • Experience: 8-10 years of progressively responsible experience in Information Technology operations and system design, ideally within an academic, government lab, or corporate R&D research setting.

  • Preferred Experience: 5+ years of experience explicitly leading, architecting, and supporting multi-node HPC cluster environments.

D. PHYSICAL DEMANDS
  • Routinely perform server installation, troubleshooting, and repairs at the data center, including lifting or moving objects up to 50 pounds.

  • Considerable time spent at a desk using a computer terminal.

  • Ability to meet in-person with researchers and colleagues on the Santa Clara University campus.

E. WORK ENVIRONMENT
  • Hybrid Eligible: Regular on-site presence required, typically at least 3-4 days a week, depending on task requirements.

  • Occasional exposure to data center conditions, including equipment noise (>80dB), high voltage electricity, and varying temperatures.

  • Standard work hours are 9 am - 5 pm Pacific, with occasional evening or weekend work required for system maintenance or outage mitigation.


Telecommute

Santa Clara University is registered to do business in the following states: California, Nevada, Oregon, Washington, Arizona, and Illinois. Employees approved to telecommute are required to perform their work within one of these states.

EEO Statement

Equal Opportunity/Notice of Nondiscrimination

Santa Clara University is an equal opportunity employer. All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, color, ethnicity, national origin, citizenship, ancestry, religion, age, sex, sexual orientation, gender, gender expression, gender identity, marital status, parental status, veteran or military status, physical or mental disability, medical conditions, pregnancy or related conditions, reproductive health decision making, or any other characteristic protected by federal, state, or local laws. For a complete copy of Santa Clara University's equal opportunity and nondiscrimination policies, please visit the Office of Equal Opportunity and Title IX website athttps://www.scu.edu/title-ix/.

Clery Notice of Availability

Santa Clara University annually collects information about campus crimes and other reportable incidents in accordance with the federal Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act. To view the Santa Clara University report, please visit the Campus Safety Serviceswebsite. To request a paper copy please call Campus Safety at (408) 554-4441. The report includes the type of crime, venue, and number of occurrences.

Americans with Disabilities Act

Consistent with its obligations under the law, Santa Clara University will provide reasonable accommodations to applicants and employees with disabilities. Applicants who wish to request a reasonable accommodation for any part of the application or hiring process should contact the Department of Human Resources ADA Team athraccommodations@scu.eduor by phone at (408)554-4392. Please note: This contact information is intended for accommodation requests only. Resumes or inquiries about application status sent to this inbox will not be reviewed or forwarded. For resumes or questions regarding application status, please contact hrservicedesk@scu.edu.