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

Vertiv Co

Sr. Account Manager, AI Sales

Austin, TX · Remote

POSITION SUMMARY This is a remote role. preferably based out of Central US major market. The Sr. ... Maintains strong and consistent engagement with internal application engineers, lines of business ...

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Remote Hpc Engineer information

See Austin, TX salary details

$38.7K

$100.9K

$136.3K

How much do remote hpc engineer jobs pay per year?

As of Sep 12, 2026, the average yearly pay for remote hpc engineer in Austin, TX is $100,858.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,300.00 and $115,500.00 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 popular job titles related to Remote Hpc Engineer jobs in Austin, TX?

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

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

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

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

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

Remote Hpc Engineer jobs near you
Infographic showing various Remote Hpc Engineer job openings in Austin, TX as of September 2026, with employment types broken down into 85% Full Time, and 15% Contract. Highlights an 100% Remote job distribution, with an average salary of $100,858 per year, or $48.5 per hour.

Senior GPU Systems & Fabric Engineer (Remote)

Austin, TX • Remote

Bitdeer Technologies Group
See more jobs at Bitdeer Technologies Groupexternal

$180K - $320K/yr

Full-time

Posted 17 days ago

Job description

Bitdeer is a world-leading technology company for AI and Bitcoin mining infrastructure.

Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers and building AI computational infrastructure to support the AI revolution. Bitdeer handles complex processes involved in computing such as equipment procurement, transport logistics, data center design and construction, equipment management, and daily operations. Bitdeer also offers advanced cloud capabilities to customers with high demand for artificial intelligence.

Headquartered in Singapore, Bitdeer has deployed data centers across multiple countries, including the United States, Norway, Bhutan, and Ethiopia.
To learn more, visit https://ir.bitdeer.com/

Position Overview

We are seeking a Senior GPU Systems & Fabric Engineer to serve as the critical bridge between our physical GPU/network infrastructure and the Kubernetes abstraction layer. You will be responsible for creating the high-performance 'hardware foundation' that makes AI-native cloud computing possible. This role requires deep expertise in Linux kernel internals, GPU architectures, and high-speed interconnects, as you will be tasked with transforming raw, bare-metal compute resources into scalable, resilient, and multi-tenant cloud primitives. You will drive the design of our fabric layer, ensuring that our AI workloads have the low-latency, high-bandwidth environment they require to perform at industry-leading speeds.

Key Responsibilities

  • Architect and maintain integrations for NVIDIA/AMD GPU device plugins and Kubernetes Operators to expose hardware capabilities to the control plane.
  • Configure and optimize high-performance host networking stacks, including RDMA, SR-IOV, RoCEv2, and InfiniBand, ensuring line-rate throughput for distributed AI training.
  • Build and manage automated hardware remediation pipelines using DCGM telemetry to proactively identify, isolate, and reset degraded GPU/NIC components before they impact production jobs.
  • Implement and manage sophisticated GPU slicing technologies (MIG, vGPU) to enable efficient multi-tenant inference workloads and maximize cluster utilization.
  • Profile and tune kernel-level parameters, device drivers, and runtime libraries (CUDA, NCCL) to resolve bottlenecks and optimize containerized AI workloads.
  • Collaborate with the Scheduling and Storage engineering teams to ensure topology-aware placement and efficient data movement across the fabric.
  • Define and enforce operational standards for bare-metal provisioning, BIOS/firmware updates, and OS hardening within the containerized environment.
  • Lead technical investigations into complex performance issues spanning hardware, fabric, and software, providing actionable architectural insights.
  • Mentor team members and drive documentation standards for our evolving AI hardware stack.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field.
  • 5+ years of systems engineering experience, with strong proficiency in Linux kernel internals, C, or Go.
  • Hands-on experience with GPU architectures (NVIDIA H100/A100), CUDA runtimes, and distributed networking (RDMA, InfiniBand).
  • Deep understanding of containerized environments and Kubernetes device plugin architecture.
  • Proven track record of operating, debugging, and scaling bare-metal systems in large-scale production or HPC environments.
  • Familiarity with infrastructure automation (e.g., Terraform, Ansible, CI/CD pipelines) for managing hardware lifecycles.
  • Strong problem-solving skills, with the ability to navigate ambiguous performance challenges at the intersection of hardware and software.
  • Excellent communication skills, with a collaborative approach to working across infrastructure, scheduling, and reliability teams.
  • Experience working in high-velocity, high-growth engineering environments is strongly preferred

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Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, color, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.