3 hours ago
Remote, United StatesStaff+
Responsibilities
- Design, develop, and debug LustreFS features, fixes, and enhancements across major storage subsystems.
- Investigate customer and scale-related defects, drive root-cause analysis, and implement correct and maintainable fixes.
- Perform performance tuning, failure analysis, reliability improvements, and workload characterization for large-scale Lustre deployments.
- Collaborate with QE, support, and release teams to reproduce issues, improve diagnostics, and expand high-risk scenario coverage.
- Participate in code and design reviews and validate fixes through targeted testing, failure injection, log analysis, and performance characterization.
- Document subsystem behavior, debugging methods, failure patterns, operational practices, and reusable engineering lessons.
- Use AI-assisted tools to accelerate triage, debugging, code comprehension, documentation, and early-stage design.
- Mentor junior engineers and lead focused technical efforts within a subsystem.
Requirements
- 10+ years of experience in systems software, distributed systems, storage, Linux kernel, or filesystem engineering.
- Strong experience developing, supporting, or performance-engineering LustreFS with depth in at least one major subsystem.
- Strong C programming and Linux systems debugging skills.
- Working knowledge of Linux kernel internals, filesystem semantics, networking, and performance analysis.
- Experience with LNet or high-performance transports such as RDMA, InfiniBand, RoCE, or TCP-based storage networking.
- Ability to debug issues across client, server, network, and backend storage layers.
- Strong collaboration skills in a cross-functional engineering environment.
- Preferred experience in HPC, AI infrastructure, or large-scale parallel storage environments.
- Preferred familiarity with ZFS, ldiskfs, NVMe-backed storage, observability, and performance tooling.
- Preferred experience creating test plans, reproducer frameworks, runbooks, or diagnostic automation.
- Comfort using AI tools for debugging, code reviews, triage, documentation, and design ideation.
- Preferred experience mentoring junior engineers or leading focused technical efforts.
About DDN
DDN builds high-performance data storage and data management systems for AI, machine learning, and high-performance computing workloads used by enterprises, research institutions, and governments. It sells appliance hardware and software (including parallel file systems and AI data platforms) along with support and professional services. Founded in 1998 and headquartered in Chatsworth, California, the privately held company reports serving over 11,000 organizations worldwide.