Technical Lead – GPU Infrastructure

🔥 20 hours ago

🇮🇪 Ireland – Remote

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 25%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Tether.to

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2014

₿ Crypto

💳 Fintech

💸 Finance

Crypto • Fintech • Finance

Tether. to is a leading digital asset company that pioneers the use of stablecoins in the blockchain space. As the most widely adopted stablecoin, Tether tokens are designed to be pegged 1-to-1 with fiat currencies, offering a stable digital asset option for users. The platform facilitates these token transactions across multiple blockchains, enhancing cross-border transactions while maintaining transparency with daily records of total assets and reserves. Tether's initiatives include educational programs promoting digital asset usage, especially targeting regions like the Middle East, Turkey, and the Philippines. Tether thus positions itself as a disruptor in the traditional financial system by enabling a stable, efficient method of handling transactions in the digital currency world.

📋 Description

• Own the end-to-end architecture of Tether Data's Cosmic AC GPU compute and managed inference platform • Create and maintain architecture proposals, high-level designs, and low-level designs through review • Lead and line-manage approximately twelve distributed engineers across backend, frontend, DevOps, QA, and documentation • Set engineering standards, conduct code and design reviews, manage release gates, hold one-to-ones, and provide growth and performance input • Design, build, and operate a managed Slurm service for research users • Own controller and accounting, partitions and login nodes, node onboarding, driver and CUDA baselines, stalled-job and node-health detection, draining, autohealing, storage visibility, identity, and isolation • Own Kubernetes cluster bootstrap and lifecycle on partner-provided bare metal • Manage NVIDIA GPU Operator, Network Operator, VM-based GPU isolation, KubeVirt, VFIO, upgrades, backup and recovery, and node replacement • Own managed inference architecture, multi-GPU and multi-node parallelism, autoscaling, request routing, endpoint reliability, and confidential-compute-capable capacity • Establish metrics, logging, alerting, and SLOs across control plane, GPU fleet, and application tiers • Lead incident response, post-incident reviews, and a sustainable on-call model • Serve as primary technical interface to infrastructure partners and vendors • Translate requirements into written specifications and acceptance tests, manage escalations, and contribute to capacity planning and hardware sourcing • Work with research, model-training, and product teams to translate workloads into platform requirements and broker scarce capacity • Complete the platform team and set the technical bar for new engineers • Own implementation and delivery plans within a fixed first-six-month delivery window

🎯 Requirements

• Eight or more years of hands-on engineering experience • At least three years leading teams that build and operate infrastructure platforms other teams depend on • Bachelor's or Master's degree in computer science or engineering, or equivalent practical experience • Hands-on experience operating Slurm at scale, including slurmctld, slurmdbd, partitions, QoS, priority, accounting, prolog and epilog, node health scripting, and upgrades with jobs running • Experience operating an HPC or GPU training cluster for a research population is ideally desired • Experience operating NVIDIA GPU fleets on bare metal, including driver and CUDA lifecycle, Fabric Manager, NVSwitch, DCGM, MIG, node burn-in, and acceptance • Experience with InfiniBand, subnet configuration, RDMA, SR-IOV, and diagnosing multi-node NCCL performance problems • Deep Linux systems knowledge, including kernel modules and drivers, PCIe passthrough, vfio-pci, cgroups, namespaces, and performance tuning • Production Kubernetes operation, including control plane, upgrades, CNI, CSI, operators, custom controllers, and multi-tenancy design • Experience with HPC storage and data movement, including VAST, Lustre, NFS, node-local NVMe caching, and distributing large model weights and datasets • Experience with Prometheus, Grafana, Loki or equivalents, SLOs, incident response, and post-incident review • Working fluency in JavaScript and Node.js sufficient to review control plane, CLI, and worker services and make architecture decisions • Experience delivering a multi-tenant IaaS, PaaS, or research computing service with resource isolation, quotas, usage metering, and user-facing API and CLI surfaces • People management across time zones, cross-track review, written architecture decisions, and ability to challenge partners or executives with reasons • Excellent written and spoken English • Fully remote location based between UTC and UTC+5:30 • Occasional travel to partner sites and team events • Desirable experience with Slurm operators on Kubernetes or Kubernetes-native schedulers • Desirable experience with modern serving stacks such as vLLM, SGLang, and TensorRT-LLM • Desirable experience with VM and container isolation, confidential computing, Cluster API, kubeadm, Cilium, NVSentinel-class autohealing, infrastructure as code, GitOps, GPU cloud/HPC/AI lab platforms, distributed systems, and hardware-provider relationships

🏖️ Benefits

• Fully remote work • Occasional travel to partner sites and team events