3 months ago
Santa Clara, CA, USAStaff+
Responsibilities
- Design, develop, and optimize high-performance storage I/O paths for throughput, latency, and concurrency.
- Build distributed storage components for erasure coding, data protection, recovery, replication, and data layout.
- Develop scalable concurrency models, locking mechanisms, and fault-tolerant designs.
- Analyze, profile, benchmark, and tune performance across CPU, memory, caching, scheduling, data movement, multi-node, and multi-device environments.
- Design asynchronous, event-driven architectures supporting AI workloads, high-speed data pipelines, and real-time analytics.
- Lead architecture decisions, design reviews, code reviews, complex debugging, and technical strategy for the I/O Path team.
- Mentor engineers and promote engineering excellence through technical reviews and strong engineering practices.
- Collaborate with QE, storage, networking, performance, field, and support teams to deliver reliable enterprise software.
- Improve validation strategies, quality coverage, automation, release processes, and software delivery reliability.
- Debug customer and system issues and translate findings into product improvements.
Requirements
- 15+ years of experience developing large-scale systems software using C/C++.
- 10+ years of hands-on experience designing and developing storage systems, distributed storage platforms, or high-performance I/O subsystems.
- Deep knowledge of storage architecture, I/O optimization, memory management, caching, scheduling, and data path design.
- Experience with erasure coding, replication, recovery, fault tolerance, concurrency, synchronization, and distributed systems.
- Hands-on experience with SPDK or similar high-performance user-space storage frameworks.
- Expertise in performance analysis, profiling, debugging, and system optimization.
- Preferred experience with HPC, AI infrastructure, large-scale storage platforms, distributed file systems, object storage, or hybrid storage architectures.
- Preferred knowledge of NVMe-oF, RDMA, and high-speed networking technologies.
- Preferred experience building observability, monitoring, and self-healing infrastructure.
- Preferred familiarity with containerized workloads and cluster orchestration.
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.