Software Engineer, DGX Cloud AI Infrastructure

🕒 4 dias atrás

🏄 California, Oregon, +2 estados a mais – Remoto

🏄 California – Remote 🌲 Oregon – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $116.000 - $189.750 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

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NVIDIA

SiteLinkedInTodas as Vagas

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

• Bring up, validate, and debug large-scale AI clusters, infrastructure, and end-to-end workloads • Bring up, tune, and benchmark AI pre-training, post-training, and inference workloads using PyTorch, NeMo / Megatron, TensorRT-LLM, and adjacent NVIDIA AI software stacks • Perform root-cause analysis of failures in large distributed environments • Contribute to resilience and failure-attribution tooling that detects, triages, and attributes node, fabric, and workload failures across the cluster • Build and maintain repeatable benchmark suites, automation, acceptance criteria, and qualification workflows on new platforms • Tune runtime settings, communication parameters, and deployment configurations in partnership with framework, systems, and platform teams • Deliver actionable, data-driven recommendations based on profiling, benchmark results, and cluster characterization

🎯 Requisitos

• Bachelor’s or Master’s in Computer Science or a related technical field, or equivalent experience • 3+ years of experience developing software for AI, HPC, or systems-level applications • Hands-on experience with multi-GPU or multi-node workloads and CUDA-aware distributed execution • Background with debugging and scaling distributed systems • Experience debugging and triaging AI applications across the full stack, from application level toward hardware • Experience operating workloads in scheduled, containerized cluster environments • Excellent analytical, debugging, and communication skills, with a collaborative approach across teams • Strong Python and C/C++ programming skills • Hands-on experience with NCCL and CUDA-aware distributed execution • Familiarity with RDMA software stack, including NCCL, IB verbs, UCX, and libfabric • Familiarity with InfiniBand / RoCE congestion debugging • Experience building acceptance tests, benchmark harnesses, regression gates, or cluster qualification tooling for AI platforms, including MLPerf • Experience diagnosing performance jitter • Experience building resilience, fault-detection, or failure-attribution systems for datacenter-scale infrastructure

🏖️ Benefícios

• Equity • Benefits