Unified data platform for AI workloads across edge, data centers, and clouds
Hammerspace abstracts unstructured data across distributed infrastructure—edge sites, on-premises data centers, and public clouds—using a stack built on Kubernetes, NFS, and custom C++/Go orchestration layers. The company is shipping infrastructure-level tooling (Ansible, Terraform, NVMe-oF, InfiniBand) to solve real-time data-access bottlenecks for AI and HPC workloads. Hiring is weighted toward senior engineers (10 of 12 open roles) and sales, with channel strategy a priority—suggesting a transition from direct sales toward partner-led growth at scale.
Notable leadership hires: Channel Sales Director
Hammerspace builds a data orchestration platform that unifies unstructured data across heterogeneous storage and compute environments. The product eliminates data silos by making datasets instantly accessible to users, applications, and GPU clusters regardless of physical location—critical for enterprises running AI training pipelines and high-performance analytics across multiple sites. Founded in 2018 and based in Redwood City, the company operates in the 201–500 employee range and actively hires in the United States, United Kingdom, and United Arab Emirates. Core pain points center on latency-sensitive data access, last-mile integration friction, and customer ROI realization—operational challenges that map directly to their product roadmap around performance optimization and enablement.
Kubernetes, Python, Go, C++, NFS, NVMe-oF, InfiniBand, Docker, Terraform, Ansible, KVM, and RAID. Cloud integrations span AWS, Azure, and GCP. Sales stack includes Salesforce, Outreach, and LinkedIn Sales Navigator.
Redwood City, California. The company was founded in 2018 and is privately held with 201–500 employees.
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Hammerspace's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.