At DDN, you will work on problems that sit at the heart of modern infrastructure:
Scaling and optimizing Network File Systems
Building and improving distributed file systems and object storage
Tuning performance across kernel-level and user-space I/O stacks
Working with NVMe, SSDs, RDMA, and high-speed networking
Integrating storage platforms into Kubernetes-native environments
Using Python to automate, debug, test, and improve complex systems
Your work will directly influence how high-performance data platforms behave under real-world load, not just in theory.
What you’ll doDesign, build, and optimize features across DDN’s NFS and storage stack
Diagnose bottlenecks across file systems, storage media, networking, and I/O paths
Improve performance, scalability, and resiliency in distributed storage environments
Work across kernel-space and user-space components to solve hard systems problems
Collaborate with engineers across storage, systems, and platform layers
Develop tooling and automation in Python to improve observability, testing, and operations
Help shape the next generation of infrastructure for AI and data-intensive workloads
Strong hands-on experience with Network File Systems (NFS)
Deep understanding of distributed file systems
Experience with object storage
Production experience with Kubernetes
Strong Python skills
Experience working on kernel-level and/or user-space I/O stacks
Familiarity with NVMe, SSDs, RDMA, and high-speed networking
A systems mindset: you know how to debug complex performance and reliability issues across layers
You are energized by low-level systems work
You like solving problems most engineers avoid because they are too deep, too subtle, or too performance-sensitive
You care about the details of how storage and networking behave under pressure
You want your work to matter in environments where performance is mission-critical
Your background is primarily general backend, SRE, or platform engineering without deep storage/filesystem ownership
You’ve used storage systems, but haven’t built or debugged them at a systems level
You prefer abstraction layers over getting hands-on with performance, I/O paths, and infrastructure internals
You want a role focused on coordination more than engineering depth
Skills Required
- Strong hands-on experience with Network File Systems (NFS)
- Deep understanding of distributed file systems
- Experience with object storage
- Production experience with Kubernetes
- Strong Python skills
- Experience working on kernel-level and/or user-space I/O stacks
- Familiarity with NVMe, SSDs, RDMA, and high-speed networking
- Ability to debug complex performance and reliability issues across system layers
What We Do
DDN is the world’s largest private data storage company and the leading provider of intelligent technology and infrastructure solutions for Enterprise At Scale, AI and analytics, HPC, government and academia customers. Through its DDN and Tintri divisions, the company delivers AI, Data Management software and hardware solutions, and unified analytics frameworks to solve complex business challenges for data-intensive, global organizations. DDN provides its enterprise customers with the most flexible, efficient and reliable data storage solutions for on-premises and multi-cloud environments at any scale. Over the last two decades, DDN has established itself as the data management provider of choice for over 11,000 enterprises, government, and public-sector customers, including many of the world’s leading financial services firms, life science organizations, manufacturing and energy companies, research facilities, and web and cloud service providers.
