Senior Storage Software Engineer, DGXC Data Services

🕒 Julho 6

🗣️🇺🇸🇬🇧 Inglês obrigatório

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Logo of NVIDIA

NVIDIA

10.000+ funcionários

Fundada em 1993

🏥 Saúde

🏭 Manufatura

🤖 Inteligência Artificial

Healthcare • Manufacturing • Artificial Intelligence

A NVIDIA é uma empresa de tecnologia líder, especializada em computação acelerada e inteligência artificial. A companhia é pioneira em avanços em unidades de processamento gráfico (GPUs), computação em nuvem, data centers e realidade virtual, com foco nos setores de games, automotivo, saúde e robótica. As inovações da empresa, como o NVIDIA Omniverse, transformam processos digitais tradicionais ao viabilizar simulações de alta fidelidade e tarefas de renderização. Suas aplicações abrangem diversos setores, desde veículos autônomos com o NVIDIA DRIVE até soluções de saúde com o NVIDIA Clara, além de análises e fluxos de trabalho impulsionados por IA.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• equity • benefits

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