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Remote Hpc Engineer Jobs (NOW HIRING)

Staff HPC Infrastructure Engineer

$110K - $144K/yr

The HPC engineering team is looking for a Staff-level engineer with broad, all-round HPC competency ... Remote-USA-CA Primary Location Base Pay Range: $155,700 - $214,150 Other US Location(s) Base Pay ...

HPC Performance Engineer

Seattle, WA · On-site +1

$165K - $242K/yr

CoreWeave is seeking a highly skilled and motivated HPC Performance Engineer to join our HAVOCK ... Ability to effectively prioritize and communicate proposed features and fixes in a remote-employee ...

... Applications Engineer to join the Applications team, with demonstrated ability in moving HPC ... Remote considered for exceptional candidates. As part of a software-defined hardware company, you ...

CoreWeave is seeking a highly skilled and motivated HPC Performance Engineer to join our HAVOCK ... Ability to effectively prioritize and communicate proposed features and fixes in a remote-employee ...

CoreWeave is seeking a highly skilled and motivated HPC Performance Engineer to join our HAVOCK ... Ability to effectively prioritize and communicate proposed features and fixes in a remote-employee ...

New

CoreWeave is seeking a highly skilled and motivated HPC Performance Engineer to join our HAVOCK ... Ability to effectively prioritize and communicate proposed features and fixes in a remote-employee ...

HPC Software Engineer III - UPDATED

Green Bank, WV · On-site +1

$46.75 - $63/hr

For well qualified candidates, a remote work arrangement may be considered. What You Will be Doing ... Work with HPC system engineers to tune application performance for specific architectures.

HPC Software Engineer III - UPDATED

Socorro, NM · On-site +1

$54.25 - $72.75/hr

For well qualified candidates, a remote work arrangement may be considered. What You Will be Doing ... Work with HPC system engineers to tune application performance for specific architectures.

Location : Hybrid in either our Austin, TX or Minneapolis, MN offices preferred but Remote ... programming models and languages such as MPI, OpenMP, CUDA, or OpenACC * Familiarity with HPC ...

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Remote Hpc Engineer information

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$39K

$101.8K

$137.5K

How much do remote hpc engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for remote hpc engineer in the United States is $101,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $116,500.00 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.

More about Remote Hpc Engineer jobs

What cities are hiring for Remote Hpc Engineer jobs?

Cities with the most Remote Hpc Engineer job openings:

What are the most commonly searched types of Hpc Engineer jobs?

The most popular types of Hpc Engineer jobs are:

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States with the most job openings for Remote Hpc Engineer jobs include:

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

Infographic showing various Remote Hpc Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 92% Full Time, 3% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $101,752 per year, or $48.9 per hour.

Staff Slurm Cluster & HPC Engineer (Remote)

Austin, TX • Remote

$180K - $260K/yr

Full-time

Posted 15 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 Staff Slurm Cluster & HPC Scheduling Engineer to own Slurm as a first-class, productized scheduling layer across that fleet. This person is the single technical owner of Slurm cluster architecture, multi-tenant scheduling policy, and cluster reliability on both bare-metal and VM-based GPU nodes, and will lead our adoption of the Slinky operator stack (slurm-operator, and slurm-bridge where it fits) so that Slurm and Kubernetes workloads can share the same GPU pool. The role is deeply hands-on, customer-facing during onboarding and escalations, and sets the engineering standard the rest of the platform team builds on.

Key Responsibilities

  • Slurm cluster architecture and lifecycle Design, deploy, and operate production Slurm clusters on bare metal and VMs: slurmctld/slurmdbd high availability, slurmrestd, configless slurmd, SACK/MUNGE and JWT authentication, and rolling version upgrades on live clusters without losing running jobs.
  • Topology-aware scheduling for GPU fabrics Model the physical fabric in topology.conf topology/tree for rail-optimized InfiniBand/RoCE designs and topology/block for NVLink domains such as GB200/GB300 NVL72 and prove placement quality with NCCL bandwidth and multi-node training validation rather than assumption.
  • Multi-tenant scheduling policy Own the account/association tree, partitions, QOS, fairshare, preemption, reservations, and per-tenant TRES limits. Enforce fail-closed defaults: an unresolved tenant identity or an empty entitlement set must deny, never degrade into unrestricted access.
  • Slinky on Kubernetes Lead implementation of the Slinky slurm-operator, including its NodeSet, LoginSet, Accounting, RestAPI, and Token custom resources, cert-manager and Helm-based delivery, shared parallel-storage mounts, and login pods running sackd/sshd. Evaluate and pilot slurm-bridge for co-scheduling Kubernetes Pods, PodGroups, Jobs, JobSets, and LeaderWorkerSets through the Slurm scheduler, and document its constraints notably exclusive whole-node allocation before any customer exposure.
  • Elastic capacity between Slurm and Kubernetes Use Slurm cloud and power-save mechanisms (ResumeProgram/SuspendProgram, SuspendTime, ResumeTimeout) together with fleet automation to shift GPU nodes between batch training queues and Kubernetes inference capacity as demand moves.
  • Container and job runtime Operate Pyxis/Enroot and OCI/containerd job paths with correct gres.conf, cgroup v2 device constraints, and CUDA_VISIBLE_DEVICES behavior; support MPI/PMIx, module/Spack environments, and customer-supplied images.
  • Cluster health and reliability engineering Build the passive and active health-check system expected of a top-tier GPU cloud: prolog/epilog checks, LBNL NHC or equivalent, DCGM diagnostics, and detection of XID/SXID errors, ECC faults, PCIe errors, GPUs falling off the bus, IB/RoCE link flaps, and NCCL stalls with automatic drain and job requeue. Own burn-in and acceptance testing for every new rack before it carries paid work.
  • Automation and infrastructure as code Deliver clusters through Terraform/Ansible, golden images, and bare-metal provisioning (PXE, Redfish, IPMI) so that a cluster build is reproducible, reviewable, and auditable rather than hand-tuned.
  • Observability, accounting, and billing integration Instrument queue wait time, allocation efficiency, GPU utilization, and job failure taxonomy through a Slurm exporter into Prometheus/Grafana; configure AccountingStorageTRES and TRESBillingWeights, and reconcile sacct/sreport GPU-hours against the platform's metering and invoicing pipeline.
  • Technical leadership and customer engagement Write runbooks and tenant-facing documentation, onboard and support enterprise customers, act as escalation point for cluster incidents, and mentor platform engineers on Slurm and HPC scheduling practice.

Qualifications

  • 8+ years in HPC, systems, or cloud infrastructure engineering, including 4+ years operating production Slurm clusters at 100+ GPU-node scale with real users and service-level commitments.
  • Deep hands-on Slurm expertise: slurm.conf, gres.conf, topology.conf, cgroup.conf, partitions/QOS/fairshare/preemption/reservations, slurmdbd accounting, slurmrestd, MUNGE/SACK and JWT authentication, and version upgrades performed on live clusters.
  • Strong GPU and fabric fundamentals: NVIDIA drivers and Fabric Manager, DCGM, MIG, InfiniBand/RoCEv2 (subnet manager/UFM, rail-optimized topology), GPUDirect RDMA, and practical NCCL tuning and failure diagnosis.
  • Production Kubernetes experience and working knowledge of the operator/CRD pattern, plus hands-on exposure to at least one Slurm-on-Kubernetes stack Slinky slurm-operator or slurm-bridge, CoreWeave SUNK, or Nebius Soperator with an informed view of the tradeoffs between them.
  • Experience delivering both bare-metal and virtualized compute: bare-metal provisioning and firmware/BIOS lifecycle management, hypervisor or VM-based clusters (KVM/QEMU or a public-cloud equivalent), and Terraform/Ansible-driven automation.
  • Working knowledge of parallel and shared storage for AI workloads Lustre, GPFS/Spectrum Scale, WEKA, VAST, or NFS and of how storage behavior shapes job performance and failure modes.
  • Proficient in Python and Bash for cluster automation; Go experience is a plus for integrating with Bitdeer AI's platform control plane and with Slurm/Slinky REST client code.
  • Multi-tenant security discipline: derives tenant scope from a verified identity rather than client-supplied fields, designs authorization to fail closed, and treats isolation across accounts, namespaces, storage, and networks as a hard requirement.
  • Clear written and verbal communication in English, with the maturity to work directly with enterprise customers and to translate scheduling and reliability tradeoffs for product, sales, and executive stakeholders

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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.