Senior Storage Software Engineer, DGXC Data Services

🕒 il y a 1 mois

🏄 California, North Carolina, +2 états de plus – Distant

🏄 California – Remote 🌲 North Carolina – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $152 000 - $241 500 / an

⏰ Temps Plein

🟠 Senior

🧑‍💻 Développeur Full-Stack

🦅 Parrain de Visa H1B

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NVIDIA

Site WebLinkedInTous les Emplois

10 000+ employés

Fondée en 1993

🏥 Santé

🏭 Fabrication

🤖 Intelligence artificielle

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA est une entreprise technologique de premier plan, spécialisée dans le calcul accéléré et l’intelligence artificielle (IA). NVIDIA est à l’avant‑garde des avancées en GPU (processeurs graphiques), cloud computing, centres de données et réalité virtuelle, avec un accent particulier sur les secteurs du gaming, de l’automobile, de la santé et de la robotique. Ses innovations, telles que NVIDIA Omniverse, transforment les processus numériques traditionnels en permettant des simulations haute fidélité et des tâches de rendu de pointe. Ses applications couvrent de nombreux secteurs, des véhicules autonomes avec NVIDIA DRIVE aux solutions de santé avec NVIDIA Clara, ainsi que des analyses et workflows pilotés par l’IA.

Description

• Build storage technologies, client libraries, and filesystem frameworks that help AI workloads access data across object stores, file systems, and hybrid cloud infrastructure. • Develop high-performance storage paths for training and inference workflows, including data loading, checkpointing, caching, POSIX-style access, and object-store integration. • Build observability systems that diagnose storage bottlenecks, attribute GPU idle time to I/O behavior, and expose actionable telemetry through production monitoring stacks. • Improve performance, scalability, and reliability of storage systems serving massive datasets, deep directory trees, and high-concurrency AI workloads. • Work closely with internal AI teams, platform teams, SRE, and operations to validate storage behavior against real workloads and production environments. • Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, performance, and verification.

🎯 Exigences

• BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience, with 5+ years of software engineering experience. • Strong foundation in algorithms, data structures, distributed systems, operating systems, and practical software design. • Experience building performance-sensitive systems, storage, backend, or cloud-native software in languages such as Go, Python, Rust, C/C++, or Java. • Experience with storage systems, object stores, caching, Linux systems, Kubernetes, or cloud infrastructure. • Ability to reason about performance, scalability, concurrency, reliability, and operational tradeoffs in production systems. • Ability to design APIs, document systems, communicate clearly, and break ambiguous infrastructure problems into practical execution plans. • Curiosity and practical judgment around AI-assisted or agentic engineering workflows, including using clear intent, specifications, acceptance criteria, tests, and verification to guide development.

🏖️ Avantages

• equity • benefits