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Remote Hpc Engineer Jobs in Houston, TX (NOW HIRING)

YO AI Labs

GPU Programmer - Remote

Houston, TX · Remote

$60 - $85/hr

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 ...

New

YO AI Labs

GPU Programming Expert - Remote

Houston, TX · Remote

$60 - $85/hr

Remote Job Overview We are seeking experienced GPU Programmers / Software Engineers to design and ... Background in graphics programming, ML acceleration, scientific computing, HPC, or related GPU ...

New

All JobsHpc Engineer JobsRemote Hpc Engineer JobsRemote Hpc Engineer Jobs in Houston, TX

Remote Hpc Engineer information

See Houston, TX salary details

$37.2K

$97.2K

$131.3K

How much do remote hpc engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote hpc engineer in Houston, TX is $97,171.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,200.00 and $111,300.00 per year, depending on experience, location, and employer.

What is a remote HPC engineer?

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 skills and qualifications are needed to be a remote HPC engineer?

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.

How do remote HPC engineers 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.

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.

What are the most commonly searched types of Hpc Engineer jobs in Houston, TX?

The most popular types of Hpc Engineer jobs in Houston, TX are:

What are popular job titles related to Remote Hpc Engineer jobs in Houston, TX?

For Remote Hpc Engineer jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Remote Hpc Engineer jobs in Houston, TX look for?

The top searched job categories for Remote Hpc Engineer jobs in Houston, TX are:

What cities near Houston, TX are hiring for Remote Hpc Engineer jobs?

Cities near Houston, TX with the most Remote Hpc Engineer job openings:

Remote Hpc Engineer jobs near you

GPU Programming Software Engineer Expert - Remote

YO AI Labs

Houston, TX • Remote

$60 - $85/hr

Full-time

Posted yesterday

New

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