Senior Software Engineer, GPU Cluster Infrastructure

🕒 il y a 1 mois

🌐 États-Unis, Singapour – Distant

🇺🇸 États-Unis – Télétravail 🇸🇬 Singapour – Télétravail

🏄 California – Distant

🏄 California – Remote

💵 $150 000 - $275 000 / an

⏰ Temps Plein

🟠 Senior

🧑‍💻 Développeur Full-Stack

👻 Score fantôme 13%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Artificial Intelligence • Education • Non-profit

Ashby Electrical Limited est une entreprise d’électricité fondée en 2018, spécialisée dans la fourniture de solutions électriques économiques et durables pour des projets résidentiels et tertiaires. L’entreprise se distingue par la qualité de ses prestations tout au long du cycle de vie des projets, incluant la conception, l’installation, les essais et la mise en service. Ashby Electrical s’engage à bâtir des relations solides avec ses clients, fondées sur la confiance, l’intégrité et le professionnalisme, afin de livrer des projets dans les délais et dans le respect des budgets.

Description

• 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

🎯 Exigences

• 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

🏖️ Avantages

• 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

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