Senior/Staff Lustre Engineer
DataDirect Networks
Senior/Staff Lustre Engineer
DataDirect Networks
High-performance storage for unstructured data
Contribute to Lustre architecture and lead implementation of new features across core subsystems including MDS/OSS, LDLM, DNE, DoM, FLD, layout, snapshot, quota, security, and recovery
Write high-performance, production-grade code across the Lustre kernel module, user-space utilities, and supporting libraries
Own the full development lifecycle for major features, from design and coding through testing, performance tuning, and upstream patch submission
Improve scalability for multi-petabyte Lustre environments, including metadata performance, I/O path optimization, and integration with modern interconnects and storage fabrics
Modernize Lustre internals through kernel API updates, locking improvements, RDMA enhancements, and cloud/container-oriented capabilities
Prototype and evaluate emerging technologies such as NVMe-oF, CXL, and other next-generation storage approaches for potential Lustre integration
Strengthen regression, stress, and performance validation using tools such as IOR, mdtest, fio, and custom Lustre test tooling
Perform deep code-level performance analysis using Lustre tracing tools, perf, lockstat, and kernel profilers
Work closely with Principal Engineers, hardware teams, and application owners to translate real workload needs into practical Lustre improvements
Mentor other developers and contribute design docs, technical guides, and engineering reviews
7+ years of progressive, hands-on Lustre software development experience
A strong track record of meaningful contributions to the Lustre codebase in production or open-source environments
Demonstrated success designing, implementing, and upstreaming Lustre features that made it into major releases
Deep understanding of Lustre internals, including MDS/OSS architecture, LDLM locking and recovery, journaling, DNE, DoM, FLD, layout, quota, and security
Expert-level C programming and strong Linux kernel development experience
Strong knowledge of distributed systems, parallel file systems, and high-performance I/O
Experience with Lustre build, development, and debugging tooling such as lctl, llstat, strace, perf, and kernel tracers
Python and/or Bash skills for tooling and automation
Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field
Clear written and verbal communication skills, with the ability to explain complex technical concepts effectively
7+ years in HPC or storage software development
Visible contributions to the Lustre open-source community, including accepted patches, LUG participation, or public technical talks
Experience running or developing Lustre in cloud environments such as AWS FSx for Lustre, Azure Lustre, or custom cloud deployments
Familiarity with adjacent systems such as Ceph, DAOS, BeeGFS, WekaIO, or GPFS
Exposure to RDMA, NVMe-oF, CXL, computational storage, or AI/ML I/O workloads
Conference presentations, technical publications, or other public engineering contributions
Have built inside Lustre itself, not just around it
Enjoy solving hard kernel, performance, and distributed systems problems
Care about code quality, upstream contribution, and long-term architectural impact
Want to work on infrastructure that operates at real scale under real performance constraints
Have mainly supported or administered Lustre rather than developed it
Come from general storage or kernel backgrounds without clear Lustre code contribution history
Prefer high-level application engineering over low-level systems and kernel work
High-performance storage for unstructured data
DDN provides high-performance data storage systems and software for data-intensive environments, including unstructured data, HPC, and AI workloads. Its products combine hardware and software to manage the data lifecycle, with A³I for GPU-optimized AI, EXAScaler as a parallel file system, IntelliFlash hybrid arrays, and Infinia for fast inference. The company differentiates itself through a dedicated focus on HPC/AI storage, close collaboration with NVIDIA, and a strategy of expanding software-defined storage and file systems via acquisitions. Its goal is to help customers scale data storage and AI workloads efficiently across enterprises, government, academia, and cloud providers.
Explore more opportunities at DataDirect Networks