Forward Deployed Engineer

🕒 March 20

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Hammerspace

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2018

☁️ SaaS

🏢 Enterprise

🤖 Artificial Intelligence

SaaS • Enterprise • Artificial Intelligence

Hammerspace is a provider of a high-performance data platform that unifies and orchestrates distributed unstructured data across on-premises, cloud, and edge storage into a single global namespace. It delivers a standards-based parallel file system, metadata-driven policy engine, and Tier 0 NVMe capabilities to accelerate AI, HPC, and GPU workloads, and is available as software, integrated appliances, and through cloud marketplaces for enterprise customers.

📋 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

🎯 Requirements

• 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

🏖️ Benefits

• N/A