Technical Lead – GPU Infrastructure

🕒 Setembro 17

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

👻 Score fantasma 25%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

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Tether.to

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2014

₿ Cripto

💳 Fintech

💸 Finanças

Crypto • Fintech • Finance

Tether. to é uma empresa líder em ativos digitais que pioneiriza o uso de stablecoins no ecossistema blockchain. Como a stablecoin mais amplamente adotada, os tokens Tether são projetados para serem lastreados 1:1 em moedas fiduciárias, oferecendo aos usuários uma opção de ativo digital estável. A plataforma facilita transações desses tokens em múltiplas blockchains, aprimorando operações transfronteiriças enquanto mantém transparência com registros diários do total de ativos e reservas. As iniciativas da Tether incluem programas educacionais que promovem o uso de ativos digitais, com foco especial em regiões como Oriente Médio, Turquia e Filipinas. Assim, a Tether se posiciona como um agente de disrupção no sistema financeiro tradicional ao viabilizar um método estável e eficiente de realizar transações no mundo das moedas digitais.

Descrição

• Own Cosmic AC platform architecture end to end through architecture proposals, high-level and low-level designs, reviews, and baseline maintenance • Lead and line-manage approximately twelve distributed engineers across backend, frontend, DevOps, QA, and documentation • Establish 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 Slurm controller/accounting, partitions, login nodes, node onboarding, driver/CUDA baselines, stalled-job and node-health detection, drain, autohealing, storage visibility, identity, and isolation • Own Kubernetes cluster bootstrap and lifecycle on partner bare metal, NVIDIA GPU Operator and Network Operator, VM-based GPU isolation, and day-2 operations • Define managed inference architecture, multi-GPU and multi-node parallelism, autoscaling, request routing, endpoint reliability, and confidential-compute-capable capacity • Establish metrics, logging, alerting, SLOs, incident response, post-incident reviews, and sustainable on-call operations • Serve as primary technical interface to infrastructure partners and vendors • Translate requirements into written specifications and acceptance tests, run escalations to closure, and support capacity planning and hardware sourcing • Work with research, model-training, and product teams to translate workloads into platform requirements and broker capacity • Complete the platform team and set the technical bar for new engineers

🎯 Requisitos

• 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 running Slurm at scale, including slurmctld, slurmdbd, partitions, QoS and priority, accounting, prolog and epilog, node health scripting, and upgrades with jobs on the system • Experience operating an HPC or GPU training cluster for a research population is ideally required • Experience operating NVIDIA GPU fleets on bare metal, including NVIDIA 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 issues • 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 shipping a platform with real users, such as multi-tenant IaaS/PaaS or research computing services • People management across time zones, cross-track review, written architecture decisions, and technical judgment with partners and executives • Excellent written and spoken English • Fully remote and based between UTC and UTC+5:30 • Desirable: Slurm operators on Kubernetes or Kubernetes-native schedulers • Desirable: modern serving stacks including vLLM, SGLang, and TensorRT-LLM • Desirable: VM/container isolation and confidential computing technologies • Desirable: Cluster API, kubeadm, Cilium, NVSentinel-class autohealing, infrastructure as code, and GitOps • Desirable: GPU cloud, HPC centre, AI lab platform, peer-to-peer, or distributed-systems experience • Desirable: hardware-provider relationship and written contract/acceptance-test experience

🏖️ Benefícios

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