Senior Solutions Architect, Robotics Foundation Model Training

🕒 Agosto 27

🏄 California – Remoto

🏄 California – Remote

💵 $152.000 - $287.500 / ano

⏰ Tempo Integral

🟠 Sênior

💻 Engenheiro de Soluções

🦅 Patrocina Visto H1B

Esta empresa já patrocinou vistos H1B no passado.

👻 Score fantasma 13%

O que significa: a chance de ninguém estar realmente contratando para esta vaga.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Por que essa pontuação:

• Aberta há 75 dias.
• As vagas desta empresa costumam ser preenchidas em 36 dias.

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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

• Engage with researchers and ML engineers to architect and optimize end-to-end training workflows for robotics foundation models, including World Models, VLAs, and WAMs • Build proof-of-concepts, reference architectures, and agentic workflows to accelerate experimentation, benchmarking, and model improvement of NVIDIA’s robotics open model platforms, including Cosmos and GR00T • Scale pre-training, fine-tuning, and reinforcement learning workloads across multi-GPU and multi-node systems • Improve utilization, throughput, and memory efficiency • Identify and eliminate data pipeline bottlenecks across storage, networking, preprocessing, and data loading for multimodal datasets including video, sensor data, and trajectories • Collaborate with NVIDIA product and engineering teams to provide feedback shaping future Physical AI platforms • Work across research, engineering, and customer teams, influencing product direction and applied AI adoption

🎯 Requisitos

• MS, PhD, or equivalent experience in Computer Science, Artificial Intelligence, Electrical or Computer Engineering, Robotics, or a related field • 5+ years of industry or research experience in deep learning, distributed computing, or large-scale model training • Hands-on experience training or optimizing multimodal or foundation models, ideally in robotics settings • Experience across the AI model lifecycle, including pre-training, supervised fine-tuning, RL or other post-training methods, evaluation, and model optimization • Strong expertise in distributed training techniques, including data/model/pipeline parallelism, sharding, and checkpointing, on multi-GPU or multi-node systems • Expertise with multimodal training frameworks such as PyTorch, NVIDIA NeMo, JAX, or Hugging Face Transformers • Experience building or working with high-throughput data pipelines for large-scale training, including storage bandwidth, network throughput, and preprocessing such as decoding, tokenization, and batching • Strong communication skills with the ability to effectively collaborate across Researchers, Engineers, and executives • Familiarity with NVIDIA AI and robotics platforms such as Cosmos, GR00T, NeMo, Isaac Sim, and Isaac Lab • Experience with robotics AI workloads, including reinforcement learning in simulation and synthetic data generation • Experience profiling and optimizing workloads using Nsight Systems, Nsight Compute, or PyTorch Profiler • Demonstrated impact improving training efficiency and scaling performance • Experience building agentic workflows for automated experimentation, model evaluation, data analysis, or research acceleration

🏖️ Benefícios

• Equity • Benefits

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