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Remote Hpc System Engineer Jobs in California (NOW HIRING)

Biohub

Staff HPC Engineer

San Francisco, CA · On-site +1

We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI ... remote dev, containerization, MLOps workflows). What You'll Bring Essential * Bachelor's or ...

Endsight

System Engineer [Remote OR Hybrid]

Napa, CA · On-site +1

$38.46 - $62.50/hr

System Engineer [Remote OR Hybrid] Department: Professional Services Employment Type: Full Time Location: Napa Compensation: $38.46 - $62.50 / hour Description Location: Remote OR Hybrid You're the ...

Endsight

System Engineer [Remote OR Hybrid]

Napa, CA · On-site +1

$38.46 - $62.50/hr

Location: Remote OR Hybrid You're the kind of person who helps others succeed. You're sharp ... Career Pathing Our System Engineers are responsible for designing, implementing, and supporting a ...

Endsight

System Engineer [Remote OR Hybrid]

Napa, CA · On-site +1

$38.46 - $62.50/hr

Remote OR Hybrid You're the kind of person who helps others succeed. You're sharp, resourceful, and ... Career Pathing Purpose Our System Engineers are responsible for designing, implementing, and ...

Mercor

Network System Engineer

San Francisco, CA · Remote

$50 - $70/hr

Position: Network Engineer - Data for Autonomous Systems annotation Type: Contract Compensation ... Remote Commitment: 30-40 hours/week Role Responsibilities * Review real-world data from deployed ...

Amat

System Engineer V - (E5)

Santa Clara, CA · On-site +1

$176K - $242K/yr

As a Systems Engineer, you'll design, integrate, and optimize complex systems that drive the ... Provide remote and onsite support to field support personnel as required Minimum Qualifications:

1mind

AI System Engineer

San Francisco, CA · On-site +1

$175K - $250K/yr

... for an AI Systems Engineer to design and build the technical foundation powering 1mind ... San Francisco preferred, open to remote (U.S.) Employment Type: Full-time [Please note that all ...

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Remote Hpc System Engineer information

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

To thrive as a Remote HPC System Engineer, you need expertise in Linux system administration, parallel computing, networking, and a degree in computer science or related field. Familiarity with job schedulers (like Slurm), cluster management tools, scripting languages (such as Python or Bash), and certifications like CompTIA Linux+ or Red Hat Certified Engineer are highly valuable. Strong problem-solving abilities, effective communication, and self-motivation are essential soft skills for remote collaboration and troubleshooting. These skills ensure the reliable operation, optimization, and scalability of HPC systems in distributed environments.

What are some common challenges faced by Remote HPC System Engineers, and how can they be managed effectively?

Remote HPC System Engineers often encounter challenges such as troubleshooting complex hardware or software issues without physical access, ensuring seamless system performance, and coordinating with geographically dispersed teams. These can be managed by leveraging strong remote monitoring tools, maintaining clear documentation, and establishing effective communication channels with on-site staff. Proactively scheduling regular system health checks and participating in virtual team meetings can also help address problems quickly and maintain high system reliability.

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

AspectRemote Hpc System EngineerRemote Cloud Infrastructure Engineer
CredentialsTypically requires Linux certifications, HPC-specific trainingOften requires cloud platform certifications (AWS, Azure, GCP)
Work EnvironmentHigh-performance computing clusters, research labsCloud platforms, data centers, virtualized environments
Industry UsageResearch, scientific computing, academiaTech, finance, enterprise IT
Search/Comparison IntentUnderstanding HPC-specific roles vs cloud rolesComparing on-premise HPC vs cloud infrastructure

The Remote Hpc System Engineer focuses on managing and optimizing high-performance computing clusters, often in research or scientific environments. In contrast, the Remote Cloud Infrastructure Engineer specializes in designing and maintaining cloud-based infrastructure across various industries. While both roles require technical expertise in system management, their environments and certifications differ, catering to distinct operational needs.

What are Remote HPC System Engineers?

Remote HPC (High Performance Computing) System Engineers are IT professionals who design, implement, manage, and troubleshoot HPC systems and clusters from a remote location. They work with advanced computing infrastructure that supports scientific research, complex simulations, and large-scale data processing. Their responsibilities include configuring hardware and software, monitoring system performance, ensuring security, and providing technical support to users, all while working off-site. This role requires strong expertise in HPC technologies, operating systems like Linux, networking, and scripting, as well as effective communication skills for collaborating with distributed teams.
What are the most commonly searched types of Hpc System Engineer jobs in California? The most popular types of Hpc System Engineer jobs in California are:
What are popular job titles related to Remote Hpc System Engineer jobs in California? For Remote Hpc System Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Hpc System Engineer jobs in California look for? The top searched job categories for Remote Hpc System Engineer jobs in California are:
What cities in California are hiring for Remote Hpc System Engineer jobs? Cities in California with the most Remote Hpc System Engineer job openings:
Remote Hpc System Engineer jobs near you
Infographic showing various Remote Hpc System Engineer job openings in California as of June 2026, with employment types broken down into 5% As Needed, 86% Full Time, and 9% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.

Staff HPC Engineer

Biohub

San Francisco, CA • On-site, Remote

Full-time

Retirement, PTO

Posted 23 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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