Overview
If you know where NFS breaks at scale — and you enjoy fixing it deep in the storage stack — this is the kind of role that rarely comes along.
DDN is building infrastructure for some of the world’s most demanding AI, data, and performance-intensive environments. We are looking for a Bay Area–based NFS Engineer who wants to work where distributed systems, file systems, object storage, Kubernetes, and high-speed networking all collide.
This is not a role for someone who has only touched storage from the outside. It is for an engineer who has lived close to the metal, understands how data moves through kernel and user-space I/O paths, and wants to push performance, reliability, and scale in real production systems.
Job Description
Why this role is compelling
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 do
- Design, 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
What we’re looking for
- 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’ll thrive here if
- 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
This role is probably not for you if
- 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
Salary Range: $150,000 - $250,000
DDN
Why DDN - DDN is where serious infrastructure engineers go to work on serious data problems. If you want to be part of a team solving challenges at the intersection of storage, distributed systems, and performance engineering — and you want to do it in an environment that values technical depth — we should talk.
Apply if - You’re a Bay Area or RTP based engineer with deep NFS and storage systems expertise, and you want to build technology that operates at the highest levels of scale and performance.
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