Senior Staff Engineer – AI Data Path

🕒 il y a 1 mois

🇺🇸 États-Unis – Télétravail

⏰ Temps Plein

🟠 Senior

🧑‍💻 Développeur Full-Stack

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DDN

Site WebLinkedInTous les Emplois

1001 - 5000 employés

Fondée en 1998

🤖 Intelligence artificielle

💰 €10 000 000 Funding Round en 2011-06

Artificial Intelligence • Data Center and Cloud Computing • High Performance Computing

DDN est un leader mondial des solutions de Data Intelligence pour l’IA, offrant des technologies de calcul haute performance (HPC) et de gestion avancée des données. Axés sur l’accélération des déploiements d’IA et de l’analytique avancée, les produits de DDN, dont la Data Intelligence Platform et des systèmes de stockage avancés, servent des secteurs variés tels que la santé, les services financiers et le secteur public. DDN s’engage à transformer l’infrastructure data des entreprises afin d’exploiter tout le potentiel de l’IA et d’améliorer l’efficacité opérationnelle.

Description

• Lead the design and implementation of high-performance data movement pipelines using NVIDIA NIXL across GPU, CPU, and storage tiers • Architect and drive integration of DDN Infinia with GPU-accelerated inference platforms for large-scale, real-time AI workloads • Own end-to-end optimization of I/O paths between GPU memory and storage using technologies such as NVIDIA GPUDirect Storage, RDMA, and NVMe-over-Fabrics • Define and implement multi-tier storage architectures (NVMe, SSD, object storage) optimized for inference latency, throughput, and scalability • Lead development of advanced KV cache management strategies, including offloading, prefetching, and persistence across distributed storage layers • Partner with AI/ML engineering teams to optimize inference performance in frameworks such as PyTorch and TensorFlow • Establish benchmarking frameworks and lead performance tuning efforts for storage and data movement in production inference environments • Diagnose and resolve complex system bottlenecks across storage, networking, and GPU subsystems • Influence architecture decisions for distributed inference systems, ensuring scalability, resilience, and efficient data locality • Drive engineering excellence through best practices in observability, performance monitoring, automation, and reliability engineering • Mentor junior engineers and provide technical leadership across cross-functional teams

🎯 Exigences

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field • 12+ years of experience in storage systems, distributed systems, or performance engineering • Proven track record of architecting and delivering large-scale, high-performance infrastructure systems • Deep expertise in distributed storage architectures (object storage, scalable file systems, or cloud-native storage platforms) • Strong understanding of Linux I/O stack, filesystem internals, and storage protocols • Extensive hands-on experience with NVMe, SSD optimization, and high-performance storage environments • Strong experience with RDMA, InfiniBand, or other high-speed data transfer technologies • Solid understanding of GPU computing concepts and CPU–GPU data movement patterns • Proficiency in Python and/or C/C++, with advanced debugging, profiling, and performance tuning skills • Demonstrated ability to optimize latency-sensitive, high-throughput production systems.

🏖️ Avantages

• Dynamic and driven team structure • Engineering excellence opportunities • Mentoring of junior engineers • Opportunity for strong prioritization skills development • Hands-on involvement across various areas