DDN builds storage and data-intelligence systems for AI workloads and high-performance computing, with a stack heavy in distributed storage (Ceph, Lustre, MinIO, Scality), container orchestration (Kubernetes, Docker), and observability (Prometheus, Grafana). The company is actively adopting Ray Data and PyTorch while expanding GPU acceleration (GPU Direct Storage), signaling a shift toward GPU-native data pipelines. Engineering dominates the org chart and hiring velocity remains steady across a global footprint—matching the complexity of validating HPC/AI storage at scale.
Tech Stack 82 technologies
What DDN Is Building
◆Challenges
- Troubleshooting complex data infrastructure challenges
- High performance and scalability
- Improving automation
- Customer issues
- Tackling challenging ai workloads
- Ensuring quality of large-scale distributed data platform
- Long complex sales cycle
- Channel partner dependency
- High-severity support cases
- Optimizing gpu utilization
▲Active Projects
- Ai account development
- Promoting ai factory reference designs
- Validation of high-performance storage solutions for hpc and ai markets
- Developing connectors to data streaming frameworks
- Distributed system test strategy
- Automated multi-tenant test suites
- Automation frameworks
- Planning framework development for business model evolution
- Shape infrastructure as code
- Build acceleration solutions with nexus/jfrog artifactory
Hiring Activity
Steady90 roles · 35 in 30d
Department
Seniority
Notable leadership hires: Lead Architect
Company intelligence
