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Remote Hpc Engineer Jobs (NOW HIRING)

Biohub

Staff HPC Engineer

San Francisco, CA · On-site +1

The Team The HPC Engineering team is part of the AI Compute Platform organization at Biohub, a ... remote dev, containerization, MLOps workflows). What You'll Bring Essential * Bachelor's or ...

NextSilicon

HPC Applications Engineer

Minneapolis, MN · On-site +1

... Applications Engineer to join the Applications team, with demonstrated ability in moving HPC ... Remote considered for exceptional candidates. As part of a software-defined hardware company, you ...

CoreWeave

HPC Performance Engineer

Seattle, WA · On-site +1

$165K - $242K/yr

CoreWeave is seeking a highly skilled and motivated HPC Performance Engineer to join our HAVOCK ... Ability to effectively prioritize and communicate proposed features and fixes in a remote-employee ...

CoreWeave

HPC Performance Engineer

New York, NY · Remote

CoreWeave is seeking a highly skilled and motivated HPC Performance Engineer to join our HAVOCK ... Ability to effectively prioritize and communicate proposed features and fixes in a remote-employee ...

Abaxis

HPC Platform Product Lead

Portage, MI · On-site +1

Bachelor's degree in computer science, Engineering, Information Systems, or equivalent practical ... PHYSICAL POSITION REQUIREMENTS Primarily office/remote knowledge-work role; prolonged periods of ...

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Remote Hpc Engineer information

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$39K

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$137.5K

How much do remote hpc engineer jobs pay per year?

As of Jul 30, 2026, the average yearly pay for remote hpc engineer in the United States is $101,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $116,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote HPC Engineer, and why are they important?

To thrive as a Remote HPC Engineer, you need a solid background in computer science or engineering, expertise in high-performance computing architectures, and experience with parallel programming. Familiarity with HPC job schedulers (like Slurm), Linux systems, distributed storage, and relevant certifications (such as CompTIA Linux+ or HPC-specific credentials) are commonly required. Strong problem-solving abilities, effective communication, and self-motivation are vital soft skills for addressing complex technical challenges remotely. These competencies ensure efficient system performance, seamless collaboration, and successful support of computational research or enterprise workloads.

What are Remote HPC Engineers?

Remote HPC (High Performance Computing) Engineers are professionals who design, implement, and manage high-performance computing systems, typically from a remote location. They work with powerful computer clusters and supercomputers to support complex computations in fields like scientific research, engineering, and data analysis. Their responsibilities include configuring hardware and software, optimizing system performance, troubleshooting issues, and ensuring the security and reliability of HPC resources. By working remotely, these engineers can support organizations and research teams around the world without needing to be physically present at the data center.

What is the difference between Remote Hpc Engineer vs Remote Cloud Engineer?

AspectRemote Hpc EngineerRemote Cloud Engineer
Required CredentialsBachelor's in Computer Science or related, certifications like HPC or LinuxBachelor's in Computer Science or related, cloud certifications (AWS, Azure)
Work EnvironmentHigh-performance computing clusters, research labs, data centersCloud platforms, virtual environments, cloud service providers
Employer & Industry UsageResearch institutions, scientific organizations, tech companiesTech firms, startups, enterprises using cloud infrastructure
Common Search & ComparisonYesYes

The main difference between a Remote Hpc Engineer and a Remote Cloud Engineer lies in their focus areas. Hpc Engineers specialize in high-performance computing systems used for scientific and research purposes, while Cloud Engineers focus on designing and managing cloud-based infrastructure. Both roles require technical expertise and certifications, but their work environments and industry applications differ significantly.

How do Remote HPC Engineers typically collaborate with on-site teams to manage high-performance computing clusters?

Remote HPC Engineers often rely on robust communication tools and version control systems to coordinate with on-site system administrators, researchers, and IT staff. They participate in regular virtual meetings to discuss cluster performance, resolve technical issues, and plan for upgrades or maintenance. Secure remote access protocols allow engineers to monitor, troubleshoot, and configure systems from afar, but effective collaboration also depends on clear documentation and periodic knowledge sharing sessions. Building strong relationships with on-site personnel helps ensure smooth operations and prompt resolution of any hardware or software challenges.
More about Remote Hpc Engineer jobs
What cities are hiring for Remote Hpc Engineer jobs? Cities with the most Remote Hpc Engineer job openings:
What are the most commonly searched types of Hpc Engineer jobs? The most popular types of Hpc Engineer jobs are:
What states have the most Remote Hpc Engineer jobs? States with the most job openings for Remote Hpc Engineer jobs include:
What job categories do people searching Remote Hpc Engineer jobs look for? The top searched job categories for Remote Hpc Engineer jobs are:
Remote Hpc Engineer jobs near you
Infographic showing various Remote Hpc Engineer job openings in the United States as of July 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $101,752 per year, or $48.9 per hour.

Staff HPC Engineer

Biohub

San Francisco, CA • On-site, Remote

Full-time

Retirement, PTO

Re-posted 10 days ago

Job description

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere.
The Team
The HPC Engineering team is part of the AI Compute Platform organization at Biohub, a non-profit research lab committed to open science and open-source AI. We own the design, operation, and reliability of hybrid GPU AI clusters that power frontier AI biology research: protein language models, genomic foundation models, and scientific reasoning systems built to be shared. Our infrastructure supports day-to-day AI researcher workflows. The team works at the intersection of AI tooling, distributed systems, HPC, and frontier AI, debugging deep AI infrastructure problems and building AI systems critical to the entire AI organization.
The Opportunity
We seek a Staff HPC Engineer to help lead the evolution of our advanced computing infrastructure into a next-generation hybrid HPC and AI platform. This role will help shape strategy, architecture, and operations for high-performance computing resources - including cutting-edge GPUs, large-scale storage, and high-speed networks - while enabling transformative science through AI and machine learning at scale.
You will design, implement, and optimize a unified HPC-AI ecosystem blending on-prem Slurm-managed clusters, cloud GPU resources, and containerized environments. This hybrid environment will power everything from traditional HPC workloads to large AI training jobs, generative model development, real-time inference, and data-intensive pipelines.
The successful candidate will be a thought leader in HPC infrastructure , capable of partnering with scientists, computational biologists, and software engineers to translate complex research needs into high-impact computing solutions. You will also foster adoption of emerging AI tools, and ensure our systems can scale to meet the demands of next-generation biomedical research.
What You'll Do
HPC Engineering
  • Build and support a hybrid HPC-AI environment with large-scale on-prem compute/storage and elastic cloud GPU clusters (Coreweave, AWS, GCP).
  • Architect and optimize environments for large-scale AI training and tuning, and low-latency scientific workloads.
  • Integrate MLOps and model deployment pipelines into HPC infrastructure, ensuring reproducibility and efficiency.
  • Implement advanced resource scheduling and orchestration (Slurm, Kubernetes, SUNK) optimized for mixed HPC and AI workflows.

Operational Excellence
  • Support researchers with job optimization, GPU utilization best practices, and performance tuning for AI and HPC applications.
  • Evaluate, deploy, and maintain AI/ML software stacks (e.g., PyTorch, TensorFlow, Hugging Face, RAPIDS) and HPC toolchains.
  • Ensure robust data ingest, analysis, and management capabilities for AI and HPC workloads, including integration with parallel file systems and object storage.

Collaboration & Enablement
  • Work with diverse science teams to translate research requirements into hardware/software solutions, from experimental design through publication.
  • Promote best practices for AI model training, validation, and deployment in shared computing environments.
  • Foster a culture of shared learning by running internal workshops on HPC-AI tooling (e.g., VS Code remote dev, containerization, MLOps workflows).
What You'll Bring
Essential
  • Bachelor's or advanced degree in Computer Science, AI/ML, Data Science, Systems Engineering, or related field.
  • 10+ years building and managing HPC infrastructure, with significant experience integrating AI/ML workloads.
  • Proven track record architecting environments for large-scale GPU AI training and inference in hybrid on-prem/cloud environments.
  • Deep expertise with HPC scheduling (Slurm), container orchestration (Kubernetes), and cloud GPU services.
  • Strong hands-on experience with AI frameworks (PyTorch, TensorFlow, JAX) and distributed training strategies (Horovod, DeepSpeed, Ray).
  • Knowledge of MLOps best practices, including CI/CD for ML, model registry, experiment tracking, and performance monitoring.
  • Exceptional ability to collaborate with multidisciplinary teams and communicate complex technical concepts clearly.
  • Demonstrated leadership in guiding infrastructure teams, influencing organizational strategy, and fostering adoption of new technologies.

Technical
  • Advanced Linux systems administration, HPC networking (Infiniband, Ethernet), and storage systems administration (VAST Lustre, Weka and ZFS)
  • Cloud platform expertise (Coreweave, AWS, GCP) including GPU provisioning, storage, and networking for AI workloads.
  • Proficiency in automation tools (Terraform, Ansible, Puppet), containerization (Docker, Singularity), and orchestration frameworks.
  • Strong experience debugging and troubleshooting hardware across the stack (network, GPU, compute and storage systems).
  • Strong scripting/programming skills (Python, Bash) and familiarity with version control (Git).
  • Experience integrating AI LLMs, AI coding assistants, and custom model development into HPC workflows.
Compensation
The San Francisco, CA base pay range for a new hire in this role is for a Staff HPC Engineer 214,000-$268,000 and for a Senior Staff HPC Engineer $241,000-$300,000.New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.
This position may be eligible to participate in our discretionary annual performance bonus program. Bonus eligibility and targets are determined in accordance with our total rewards philosophy and may vary by role.
Better Together
As we grow, we're excited to strengthen in-person connections and cultivate a collaborative, team-oriented environment. This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in-office days determined by the team's manager. The exact schedule will be at the hiring manager's discretion and communicated during the interview process.
Benefits for the Whole You
We're thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible.
  • Provides a generous employer match on employee 401(k) contributions to support planning for the future.
  • Paid time off to volunteer at an organization of your choice.
  • Funding for select family-forming benefits.
  • Relocation support for employees who need assistance moving

If you're interested in a role but your previous experience doesn't perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.
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