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Remote Hpc System Engineer Jobs in Norwalk, CA (NOW HIRING)

GPU Programmer - Remote Job Type: Contractor Location: Remote Job Overview We are seeking ... Background in graphics programming, ML acceleration, scientific computing, HPC, or related GPU ...

We are looking for an MSP Systems Engineer who is responsible for maintaining, supporting, and ... Configure and support Active Directory, Group Policy, DNS, DHCP, VPN, and remote access solutions.

We are looking for an MSP Systems Engineer who is responsible for maintaining, supporting, and ... Configure and support Active Directory, Group Policy, DNS, DHCP, VPN, and remote access solutions.

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a highly skilled AI/ML Systems Engineer to provide Systems Engineering and Technical Advisory (SETA) support to a mission ...

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Remote Hpc System Engineer information

See Norwalk, CA salary details

$54.8K

$130.2K

$171K

How much do remote hpc system engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote hpc system engineer in Norwalk, CA is $130,233.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,300.00 and $160,700.00 per year, depending on experience, location, and employer.

What is a remote HPC system engineer?

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 key skills and qualifications needed to thrive as a remote HPC system engineer?

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 popular job titles related to Remote Hpc System Engineer jobs in Norwalk, CA?

For Remote Hpc System Engineer jobs in Norwalk, CA, the most frequently searched job titles are:

What job categories do people searching Remote Hpc System Engineer jobs in Norwalk, CA look for?

The top searched job categories for Remote Hpc System Engineer jobs in Norwalk, CA are:

What cities near Norwalk, CA are hiring for Remote Hpc System Engineer jobs?

Cities near Norwalk, CA with the most Remote Hpc System Engineer job openings:

Infographic showing various Remote Hpc System Engineer job openings in Norwalk, CA as of June 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $130,233 per year, or $62.6 per hour.

GPU Programming Software Engineer Expert - Remote

YO AI Labs

Los Angeles, CA • Remote

$60 - $85/hr

Full-time

Posted 16 days ago


Job description

GPU Programmer / Software Engineer

Job Type: Contractor
Location: Remote

Job Overview

We are seeking experienced GPU Programmers / Software Engineers to design and optimize GPU-based tasks for AI and LLM applications. You will apply your expertise in GPU programming, performance optimization, and C++ development to build high-performance solutions.

Key Responsibilities
  • Design, implement, and optimize GPU software using CUDA, WebGPU, or GLSL.

  • Profile and optimize GPU kernels and shaders for performance and efficiency.

  • Develop host-side logic and GPU integrations using C++.

  • Create GPU-focused tasks and solutions for AI/LLM applications.

  • Analyze performance bottlenecks and implement optimization strategies.

Required Qualifications
  • Strong experience with GPU programming, particularly on NVIDIA GPUs.

  • Proficiency in CUDA, WebGPU, or GLSL.

  • Strong C++ programming skills.

  • Background in graphics programming, ML acceleration, scientific computing, HPC, or related GPU-focused fields.

  • Strong understanding of GPU architecture and performan