Forward Deployed Engineer

🕒 il y a 5 mois

🇬🇧 Royaume-Uni – Télétravail

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

👷🏻‍♀️ Ingénieur

👻 Score fantôme 33%

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🗣️🇺🇸🇬🇧 Anglais requis

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Hammerspace

51 - 200 employés

Fondée en 2018

☁️ SaaS

🏢 Entreprise

🤖 Intelligence artificielle

SaaS • Enterprise • Artificial Intelligence

Hammerspace est un fournisseur d'une plateforme de données haute performance qui unifie et orchestre les données non structurées distribuées sur les stockages sur site, cloud et à la périphérie dans un seul espace de noms global. Elle offre un système de fichiers parallèles basé sur des standards, un moteur de politique piloté par les métadonnées et des capacités NVMe de niveau 0 pour accélérer les charges de travail d'IA, HPC et GPU, et est disponible en tant que logiciel, appareils intégrés et via les marchés cloud pour les clients d'entreprise.

Description

• Act as the primary technical authority on-site, becoming an expert in the customer’s domain to identify and resolve real-world friction points before they escalate • Design and implement data architectures that accelerate AI/ML training pipelines, ensuring low-latency data access across hybrid-cloud environments • Build custom integrations, automation scripts, and "last-mile" solutions that bridge the gap between Hammerspace’s core product and the client’s bespoke infrastructure • Act as a "technical scout" to identify new business problems, expansion opportunities, and emerging workloads that Hammerspace can solve • Partner with the Rotational Sustaining Engineering team to translate field-discovered bugs into core product features • Translate complex technical hurdles into clear, actionable insights for both end-users (data scientists/IT admins) and executive leadership

🎯 Exigences

• MUST BE BASED IN THE UK • Deep understanding of GPU orchestration, AI/ML data pipelines, and high-performance file systems (NFS, SMB, S3) • Mastery of high-speed networking (InfiniBand, RoCE, 100GbE+) and the ability to debug complex routing, latency, and throughput issues in a distributed environment • Proficiency in Python, Go, or C++, with the ability to write production-grade tools and integrations that interface with Hammerspace APIs • Strong Linux internals expertise, including kernel tuning, storage stack performance, and containerization (Kubernetes/Docker) • Ability to quickly master the Global Data Environment architecture and deploy it across heterogeneous storage and cloud providers

🏖️ Avantages

• N/A

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