Principal Performance Architect

April 25

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DDN

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DDN is a global leader in AI data intelligence solutions, providing high-performance computing and sophisticated data management technologies. With a focus on accelerating AI deployments and advanced data analytics, DDN's products, including the Data Intelligence Platform and advanced storage systems, serve diverse sectors such as healthcare, financial services, and government. DDN is committed to transforming enterprise data infrastructure to leverage the full potential of AI and drive operational efficiency.

Artificial Intelligence • Data Storage • Machine Learning • Analytics • Enterprise AI

1001 - 5000 employees

Founded 1998

🤖 Artificial Intelligence

💰 $10M Funding Round on 2011-06

📋 Description

• Drive end-to-end performance analysis and optimization for Infinia. • Own the visibility, measurement, and tuning of system performance across the entire stack. • Partner with teams across engineering, architecture, and field engineering to deliver insights and innovations that drive customer value at scale. • Design and implement comprehensive performance instrumentation across the Infinia platform. • Develop and maintain end-to-end performance models that span applications and storage. • Build and execute reproducible performance tests for AI and data-intensive workloads. • Use advanced profiling and tracing tools to identify and address latency hotspots and bottlenecks. • Partner with component teams to deliver performance fixes and architectural recommendations. • Deliver clear, actionable performance summaries to engineering, product management, and field teams. • Mentor engineers on best practices in profiling, benchmarking, and performance-aware development.

🎯 Requirements

• 15+ years of experience in systems performance engineering or low-level infrastructure development. • Proven expertise in end-to-end performance debugging across distributed systems, from application logic down to I/O subsystems. • Strong background in system-level tools (e.g., perf, ftrace, bpftrace, nvme-cli, or similar). • Deep understanding of NVMe, CPU and memory hierarchy, caching, thread scheduling, and Linux kernel internals. • Experience optimizing compute- or data-intensive applications such as AI inference, search, or analytics. • Proficiency in C/C++ or Rust and scripting languages such as Python or Bash. • Excellent written and verbal communication skills, especially around technical reporting and architectural recommendations. • Familiarity with vector databases (e.g., FAISS, Milvus, Weaviate) and LLM inference pipelines. • Experience with SPDK, RDMA, or high-performance I/O libraries. • Exposure to storage telemetry, AI model performance tuning, or multi-tenant throughput optimization. • Experience working in highly scaled distributed systems or HPC environments. • This position requires participation in an on-call rotation to provide after-hours support as needed.

🏖️ Benefits

• Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, transgender, sex stereotyping, sexual orientation, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.