WEKA Tech Stack

AI-optimized storage platform for distributed machine learning infrastructure

Software Development Campbell, California 201–500 employees Founded 2013 Privately Held

WEKA operates a purpose-built storage system for AI workloads, layered on C++, Rust, and kernel-level I/O technologies (RDMA, DPDK, eBPF, NVMe). The stack spans GPU-acceleration (CUDA, vLLM), multi-cloud (AWS, Azure, GCP, OCI), and hardware partnerships (NVIDIA, HPE, Dell, Supermicro)—revealing a deep systems-engineering footprint. Sales hiring (26 roles) outpaces engineering (17) by 1.5x, paired with active projects around VAR partnerships and customer adoption, signaling transition from product-market fit to sales-driven scaling.

Tech Stack 63 technologies

Core StackC++ Rust AWS Kubernetes Python C/C++ UDP TCP InfiniBand RDMA DPDK SPDK NFS SSD NVMe GPU eBPF libfabric VLAN Azure OCI GCP RAID NVIDIA Dell Supermicro Hitachi HPE vLLM CUDA+26 more

What WEKA Is Building

◆Challenges

Legacy data silos
Fragile traditional data infrastructures
Speed and scalability for data storage
High performance io workloads
Acquiring new logos
Complex sales cycles
Building pipeline
Performance bottlenecks in kernel driver
Data safety across failure modes
Performance inefficiencies

▲Active Projects

Joint selling with var partners
Strategic sales pipeline development
Automation for deployment
Build distributed infrastructure platform
Customer adoption acceleration
Build sustainable ecosystem of weka customers
Diversity & inclusion
Distributed filesystem components for snapshots
Next-generation storage architecture
Proof-of-concept storage implementations

Hiring Activity

Accelerating55 roles · 40 in 30d

Department

Sales

Engineering

Support

Product

Executive

Marketing

Operations

Seniority

Senior

Manager

Director

Junior

Mid

Principal

Notable leadership hires: AI Inference Team Lead, Technical Lead

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About WEKA

WEKA builds storage infrastructure purpose-designed for AI and machine-learning workloads at enterprises and hyperscale operators. The platform eliminates I/O bottlenecks through a containerized, microservices architecture running on high-performance networks (InfiniBand, RDMA) and modern storage media (NVMe, SSD). Core use cases include exascale ML training, genomics analytics, and hybrid-cloud deployments. The company serves across cloud providers (AWS, Azure, GCP, OCI) and on-premises environments, with active projects targeting ecosystem development, deployment automation, and proof-of-concept acceleration.

HeadquartersCampbell, California

Company Size201–500 employees

Founded2013

Hiring MarketsUnited States, India, Israel, Germany, Sweden, China, Japan, Argentina

Frequently Asked Questions

What tech stack does WEKA use?

WEKA builds on C++, Rust, and kernel-level I/O libraries (RDMA, DPDK, eBPF, libfabric). The platform spans GPU frameworks (CUDA, vLLM, NVIDIA), multi-cloud (AWS, Azure, GCP, OCI), and hardware (Dell, HPE, Supermicro, Hitachi).

What is WEKA working on?

Current projects include distributed infrastructure for AI, deployment automation, customer adoption acceleration, distributed filesystem snapshots, next-generation storage architecture, and VAR partnership expansion.

How this profile is built

WEKA'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.