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Remote High Performance Computing Jobs in California

Cellanome

Machine Learning Engineer

San Diego, CA · On-site

$160K - $215K/yr

Possibility for Remote. Key Responsibilities: * Design, develop, and optimize advanced algorithms ... Optimize algorithms for deployment on edge devices, GPUs, and high-performance computing ...

Together AI

Solutions Architect

San Francisco, CA · On-site

$180/hr

... high-performance computing (HPC) environments. * Strong understanding of training, fine-tuning and ... of remote work. The US salary range for this full-time position is: $180-260K OTE + equity ...

Together AI

Solutions Architect

San Francisco, CA · On-site +1

$180/hr

... high-performance computing (HPC) environments. * Strong understanding of training, fine-tuning and ... of remote work. The US salary range for this full-time position is: $180-260K OTE + equity ...

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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 the most commonly searched types of High Performance Computing jobs in California? The most popular types of High Performance Computing jobs in California are:
What are popular job titles related to Remote High Performance Computing jobs in California? For Remote High Performance Computing jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote High Performance Computing jobs in California look for? The top searched job categories for Remote High Performance Computing jobs in California are:
What cities in California are hiring for Remote High Performance Computing jobs? Cities in California with the most Remote High Performance Computing job openings:
Remote High Performance Computing jobs near you

Senior/Staff Fuse Developer

Data Direct Networks

San Francisco, CA • On-site, Remote

$150K - $250K/yr

Full-time

Posted 9 days ago

Job description

Overview
If you enjoy building deep infrastructure systems where networking, storage, kernel behavior, and performance all intersect - this is the kind of role that rarely comes along.
At DDN, we build infrastructure for some of the world's most demanding AI, HPC, and large-scale data environments. We are looking for a Senior / Staff Fuse Developer who wants to work close to the systems layer - where file systems, object storage, RDMA networking, and Linux kernel behavior directly impact performance at scale.
This is not a role for someone who only consumes infrastructure. It is for engineers who understand how data moves through the stack, who care about latency and throughput, and who enjoy solving hard systems problems deep inside storage and Linux environments.
Job Description
Why this role is compelling
At DDN, you will work on infrastructure challenges that sit at the core of modern high-performance systems:
  • Building and optimizing FUSE-based file system technologies
  • Working across Linux kernel file systems and user-space infrastructure layers
  • Designing high-performance infrastructure for distributed storage environments
  • Improving how object storage systems behave under real production workloads
  • Working with RDMA networking principles and high-speed data movement
  • Solving performance bottlenecks across networking, storage, and I/O pathways
  • Developing systems-level infrastructure in C and C++
  • Building platforms that support AI, HPC, and large-scale data-intensive workloads

Your work will directly influence how large-scale infrastructure platforms perform in real-world production environments - not just in theory.
What you'll do
  • Design, build, and optimize FUSE-based infrastructure and storage components
  • Develop and improve Linux file system integrations across kernel and user-space layers
  • Work on distributed storage and object storage infrastructure systems
  • Improve scalability, resiliency, and performance across storage platforms
  • Optimize networking and data movement using RDMA principles
  • Diagnose bottlenecks across file systems, networking, memory, and I/O stacks
  • Develop infrastructure tooling and platform capabilities in C and C++
  • Work closely with systems, storage, and platform engineering teams on deeply technical infrastructure challenges
  • Help shape next-generation infrastructure platforms for AI and high-performance environments
What we're looking for
  • Strong hands-on experience developing with FUSE and Linux file systems
  • Deep understanding of Linux kernel file system architecture
  • Strong programming skills in C and C++
  • Strong understanding of POSIX file system principles
  • Experience with object storage systems and distributed infrastructure
  • Familiarity with RDMA networking principles and high-speed networking technologies
  • Experience working close to kernel-space and user-space I/O paths
  • Strong systems mindset with the ability to debug complex infrastructure and performance issues
  • Experience building or optimizing infrastructure platforms in production environments
You'll thrive here if
  • You enjoy low-level systems and infrastructure engineering
  • You care deeply about performance, scale, and reliability
  • You like solving technical problems that most engineers avoid because they are too deep or performance-sensitive
  • You enjoy understanding how storage and networking behave under pressure
  • You prefer working close to the metal instead of purely abstracted application layers
  • You want to build infrastructure that directly powers mission-critical environments
This role is probably not for you if
  • Your background is primarily application-layer or general backend development
  • You have limited experience with Linux internals, file systems, or infrastructure engineering
  • You prefer higher-level platform abstraction over systems-level development
  • You have not worked on performance-sensitive distributed systems
  • You want a coordination-heavy role rather than deep technical ownership

Salary Range: $150,000 - $250,000
DDN
Why DDN - DDN is where serious infrastructure engineers go to work on serious data problems.
If you want to work at the intersection of Linux systems, distributed storage, networking, and high-performance infrastructure - and you want to do it in an environment that values technical depth - this is a rare opportunity to build systems operating at massive scale.
Apply if - You are a Bay Area or RTP based engineer with deep systems and infrastructure expertise, and you want to help build the storage and infrastructure platforms behind modern AI and high-performance computing environments.
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