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Hpc Engineer Jobs in Austin, TX (NOW HIRING)

BitDeer

Staff Slurm Cluster & HPC Engineer

Austin, TX · On-site +1

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 ...

Posted today

Nvidia

HPC Operations Engineer

Austin, TX · Hybrid

$68K - $93K/yr

As an HPC Operations Engineer at NVIDIA, you will play a pivotal role in ensuring the flawless operation of our high-performance computing (HPC) environment. This opportunity is outstanding as you ...

NextSilicon

HPC Customer Solutions Engineer

Austin, TX · On-site +1

Join our customer success team as an HPC Customer Solutions Engineer . We are seeking a highly skilled, customer-centric individual to act as the primary link between our cutting-edge HPC technology ...

NextSilicon

HPC Customer Solutions Engineer

Austin, TX · Remote

Join our customer success team as an HPC Customer Solutions Engineer . We are seeking a highly skilled, customer-centric individual to act as the primary link between our cutting-edge HPC technology ...

Nvidia

Senior HPC Cluster Engineer

Austin, TX

$103K - $142K/yr

We are seeking a highly skilled and experienced HPC Cluster Engineer to design, deploy, and operate GPU Compute Clusters for EDA (Electronic Design Automation) and high-performance computing ...

NVIDIA

Senior HPC Storage Engineer

Austin, TX · On-site

As a Senior HPC Storage Engineer, you will lead the research, design, and implementation of innovative storage solutions for high performance computing workloads, while collaborating with teams to ...

NextSilicon

Staff HPC Applications Engineer

Austin, TX · On-site

We are looking for an experienced Staff Applications Engineer to join the Applications team, with demonstrated ability in moving HPC applications onto new platforms and in evaluating performance on ...

Next Silicon Ltd

Staff HPC Applications Engineer

Austin, TX · On-site

$120 - $160/hr

We are looking for an experienced Staff Applications Engineer to join the Applications team, with demonstrated ability in moving HPC applications onto new platforms and in evaluating performance on ...

New

NextSilicon

Staff HPC Applications Engineer

Austin, TX · On-site +1

We are looking for an experienced Staff Applications Engineer to join the Applications team, with demonstrated ability in moving HPC applications onto new platforms and in evaluating performance on ...

Hudson River Trading

HPC Network Engineer

Austin, TX · On-site

Hudson River Trading's High Performance Computing (HPC) Network Engineering team designs and engineers the low-latency communications infrastructure that underpins our incredibly large GPU and CPU ...

Socket.dev

AI/HPC Data Center Rack Design Engr

Austin, TX · On-site

$120 - $190/hr

THE ROLE We are seeking a highly skilled systems engineer to design data center rack layouts for AI/HPC clusters. This role involves evaluating and selecting rack-level compute, storage, networking ...

NextSilicon

HPC Field Applications Engineer

Austin, TX · On-site +1

We are looking for an experienced HPC and AI application field support engineer to join our pre-sales engineering team. The ideal candidate brings already a broad work experience in different ...

Nvidia

Senior HPC and LSF Operations Engineer

Austin, TX · Hybrid

$103K - $141K/yr

Experience implementing reliability engineering practices within HPC scheduling environments * Deep knowledge of job scheduling systems (LSF, Slurm, etc.) configuration tuning, scheduler internals ...

Nvidia

Senior Site Reliability Engineer - HPC

Austin, TX · On-site

$56.50 - $75/hr

Own SRE solutions endtoend, from design and implementation to operation and continuous improvement, ensuring they integrate cleanly with HPC schedulers, storage, and network fabrics. * Use IaC ...

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Hpc Engineer information

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How much do hpc engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for hpc engineer in Austin, TX is $106,982.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,700.00 and $132,300.00 per year, depending on experience, location, and employer.

What does an HPC engineer do?

An HPC (High-Performance Computing) Engineer designs, deploys, and optimizes high-performance computing systems used for intensive computational tasks. They work with parallel computing, cluster management, and performance tuning to ensure efficient processing of large-scale simulations, data analysis, and scientific research. Their role often involves configuring hardware, optimizing software, and troubleshooting issues to maximize system performance.

What are the key skills and qualifications needed to thrive as an HPC engineer?

To thrive as an HPC Engineer, you need a solid background in computer science, mathematics, or a related field, with expertise in parallel computing, Linux systems, and high-performance cluster management. Proficiency with job schedulers (like SLURM or PBS), programming languages such as C/C++ or Python, and experience with distributed file systems are highly valuable, and certifications in relevant areas can enhance your qualifications. Strong problem-solving, collaboration, and communication skills help you work efficiently within technical teams and explain complex concepts to non-experts. These skills and qualities are essential for ensuring high performance, reliability, and scalability of computing systems in scientific and enterprise settings.

What are some of the common challenges faced by HPC engineers in their day-to-day work?

HPC Engineers often encounter challenges such as optimizing performance for complex workloads, troubleshooting system failures, and efficiently managing large-scale infrastructures. You may be required to balance the needs of multiple users and projects, quickly address hardware or software issues, and stay ahead of evolving technologies. Collaboration with researchers, IT staff, and software developers is key to designing robust solutions. Overcoming these challenges helps improve computational efficiency and supports critical research and business objectives.

Are HPC engineers in demand?

HPC (High-Performance Computing) engineers are in high demand due to the increasing need for advanced computing in fields like scientific research, data analysis, and artificial intelligence. Employers seek professionals skilled in parallel programming, cluster management, and tools such as Linux and MPI, often requiring relevant certifications and experience with large-scale systems.

How much do HPC engineers make in the US?

HPC (High-Performance Computing) engineers in the US typically earn between $80,000 and $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in parallel computing, cluster management, or specific tools like MPI or CUDA can earn higher salaries.

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

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

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

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

Hpc Engineer jobs near you
Infographic showing various Hpc Engineer job openings in Austin, TX as of August 2026, with employment types broken down into 86% Full Time, and 14% Contract. Highlights an 72% In-person, 14% Hybrid, and 14% Remote job distribution, with an average salary of $106,982 per year, or $51.4 per hour.

Staff Slurm Cluster & HPC Engineer

BitDeer

Austin, TX • On-site, Remote

Full-time

Posted 16 hours ago

Posted today

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

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.

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