Latest AI JobsBrowse Jobs
RunPod logo

HPC Storage Engineer - West Coast

RunPodRemote - USAEngineering
Apply on company site
Salary
$180K - $240K USD
Job type
Full-time
Work mode
Remote
Posted
24 Sept 2026
Status
Open · checked 7d ago

About this role

RunPod seeks a remote HPC Storage Engineer to design, scale, and maintain a multi-region storage ecosystem for a rapidly growing AI infrastructure platform. This hands-on technical role suits an experienced systems professional eager to shape the future of artificial intelligence development workloads.

Role Overview

Operating within the infrastructure division, the HPC Storage Engineer manages local NVMe, network volumes, and S3-compatible object storage. Storage performance directly influences cold start velocity, training data streaming efficiency, and the reliable persistence of model weights for over a million developers globally. This remote position offers the opportunity to eliminate the gap between architectural design and operational execution, handling everything from control-plane code to capacity planning and on-call rotations.

Key Responsibilities

Own the capacity, durability, availability, and performance of network volumes, local NVMe, and S3-compatible object storage systems.
Tune the complete I/O path, including device configurations, filesystem settings, caching strategies, replication trade-offs, and client mount behaviors.
Diagnose complex performance issues end to end and lead capacity expansions, migrations, and hardware refreshes without customer-visible disruptions.
Collaborate with network teams to optimize high-throughput fabrics, MTU settings, congestion control, and RDMA/RoCE implementations.
Write production code for control-plane services, provisioning workflows, and data movement pipelines utilizing languages like Python, Go, or Rust.
Implement infrastructure as code, participate in code reviews, and extend APIs such as S3-compatible interfaces and Kubernetes constructs.
Build comprehensive dashboards, SLOs, and alerts using observability tooling to monitor IOPS, throughput, latency, and error rates.
Participate in an on-call rotation and drive blameless post-incident follow-through.

Requirements

Eight or more years of experience in infrastructure, systems, or storage engineering with substantial production storage ownership at scale.
Deep practical expertise with at least one distributed storage system such as Ceph, MinIO, Lustre, GPFS, MooseFS, WekaFS, VAST, or ZFS-based solutions.
Strong knowledge of Linux internals and the storage stack, including block layers, filesystems, page caches, iSCSI, and NVMe-oF.
Demonstrated experience building or operating S3-compatible object storage services.
Solid networking fundamentals with a history of tuning networks specifically for storage workloads.
Proficiency in writing and shipping production-grade code in Python, Go, Rust, or similar languages.
Hands-on experience designing and implementing metrics with observability tooling like Prometheus, Grafana, or Datadog.
Strong problem-solving skills under real production pressure, combined with a self-starting attitude and low-ego collaboration.

Nice to Have

Background in storage solutions designed for AI and ML workloads, including checkpointing, dataset streaming, and GPUDirect Storage.
Familiarity with Kubernetes storage internals such as CSI drivers, PV/PVC lifecycles, StatefulSets, and local persistent volumes.
Bare-metal and colocation experience covering hardware selection, firmware, and physical failure domains.
Multi-tenant environment experience managing isolation, fairness, and QoS requirements.
Previous tenure within a fast-growing cloud or infrastructure provider.

Skills and Tools

Distributed storage platforms (Ceph, MinIO, Lustre, VAsT, etc.)
Linux internals, block layer, filesystems, and NVMe
Programming languages including Python, Go, and Rust
Networking protocols, RDMA/RoCE, and high-speed fabrics
Observability and monitoring tools like Prometheus, Grafana, and Datadog

Salary and Benefits

Competitive base salary ranging from $180,000 to $240,000, determined by experience, qualifications, and location.
Meaningful equity and stock options in a fast-growing company.
Comprehensive medical, dental, and vision insurance plans.
Flexible paid time off to support work-life balance.
A $1,200 home office and equipment stipend to establish an ideal workspace.

About the Company

Runpod operates as RunPod, empowering more than one million developers globally to experiment, train, fine-tune, and scale artificial intelligence workloads on a unified platform. Following a $100M Series A funding round, the remote-first and Slack-native team moves with urgency, values high ownership, and builds the foundational infrastructure required for the next generation of AI development.

How to Apply

Interested candidates should review the full job details and submit an application directly on the official company careers page.

Skills and tech stack

PythonKubernetesRust

Questions candidates ask

Is this position remote?

Yes, this role is remote-first and based out of the USA, though applicants must be eligible to work in the United States without visa sponsorship.

What is the salary range for the HPC Storage Engineer role?

The competitive base pay ranges from $180,000 to $240,000, depending on factors like experience, qualifications, and location.

What programming languages are required?

Candidates should be proficient in writing and shipping production code in languages such as Python, Go, or Rust.

What level of experience is needed?

Applicants must have 8 or more years of experience in infrastructure, storage, or systems engineering with substantial ownership of production storage at scale.

What benefits and perks are included?

Benefits include meaningful equity and stock options, medical, dental, and vision plans, flexible PTO, and a $1,200 home office and equipment stipend.

Ready to apply?

The application is on the official RunPod careers page.

Apply on company site