Senior Software Engineer, GPU Cluster Infrastructure

🕒 3 dias atrás

🌐 Estados Unidos, Singapura – Remoto

🇺🇸 Estados Unidos – Remoto (EUA) 🇸🇬 Singapura – Remoto

🏄 California – Remoto

🏄 California – Remote

💵 $150.000 - $275.000 / ano

⏰ Tempo Integral

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

👻 Score fantasma 14%

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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FAR.AI

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2022

🤖 Inteligência Artificial

📚 Educação

🤝 Sem Fins Lucrativos

Artificial Intelligence • Education • Non-profit

A Ashby Electrical Limited é uma empreiteira estabelecida em 2018 que se especializa em fornecer soluções elétricas econômicas e sustentáveis para projetos residenciais e comerciais. A empresa se orgulha de entregar trabalho de alta qualidade ao longo do ciclo de vida do projeto, incluindo design, instalação, teste e comissionamento. A Ashby Electrical está comprometida em construir relacionamentos sólidos com seus clientes, fundamentada na confiança, integridade e profissionalismo, garantindo que os projetos sejam concluídos dentro do prazo e do orçamento.

Descrição

• Operate the Kubernetes GPU fleet day to day, including node lifecycle, upgrades, driver and image rollouts, staged changes with safe rollback, and capacity planning • Own batch scheduling and multi-tenancy, including queues, quotas, priorities, preemption, gang scheduling, and fair share across research teams • Design and run storage under the fleet, including high-performance shared filesystems, object storage tiers, quotas, and backups • Keep multi-node training runs fault-tolerant by owning node health and automated draining, debugging NCCL and fabric problems, tracking stragglers and flaky GPUs, and building checkpoint and restart patterns • Harden the platform through identity and access, network policy, secrets, workload isolation, and sandboxing for AI agents • Bring new capacity online by acceptance-testing providers on fabric, NCCL, and storage throughput, holding them to SLAs, and integrating new clusters with infrastructure as code • Work directly with research teams on infrastructure problems and turn recurring issues into platform fixes • Share the on-call rotation, runbooks, and postmortems • Collaborate with researchers and engineers to keep large-scale experiments performant and fault-tolerant

🎯 Requisitos

• 3+ years in systems or infrastructure engineering on production Linux, running GPU, HPC, or large-scale batch platforms • Owned at least one system from design through operation • Production Kubernetes experience for GPU workloads with a batch layer such as Slurm, Kueue, Volcano, or similar • Experience with quotas, priority and preemption, and node health • Experience owning infrastructure as code and observability for a production fleet • Experience with Terraform or Ansible • Experience deploying with Helm and ArgoCD • Experience monitoring with Prometheus or equivalent tools • Strong programming skills in at least one infrastructure language such as Python, Go, Rust, or C++ • Ability to write clearly for engineers, researchers, and providers • Additional relevant expertise in distributed training infrastructure, distributed storage, cluster security, scheduler internals, or multi-provider platforms is advantageous

🏖️ Benefícios

• Health Insurance - 94% of Insurance premium paid by Organization commencing within 1 month after your start date • Retirement - 401(k) plan with up to 2% match • 25 days Paid Time Off per year, accrued weekly • Up to 10 days of paid sick leave per year • Paid Bereavement, Family, Medical and Pregnancy Disability Leave • WFH stipend and work computer provided for eligible employees • Catered lunches and dinners on workdays at the Berkeley office • Work-related travel and equipment expenses are covered • Visa sponsorship for in-person employees