Senior Deep Learning Scientist, Multimodal Agentic RL

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NVIDIA is widely regarded as one of the technology industry’s most desirable employers. We lead the way in High-Performance Computing, Artificial Intelligence, and Visualization. Our core invention, the GPU, serves as the visual cortex of modern computers and powers our entire product suite. GPU deep learning ignited the modern AI era—the next great computing age—with the GPU acting as the brain for everything from robots and autonomous cars to conversational AI. Today, we are known globally as "the AI computing company." We are looking to grow our teams by bringing in the smartest people in the world. Join us at the forefront of technological advancement. NVIDIA is hiring Senior Deep Learning Scientists to advance our efforts in streaming and agentic multimodal AI. You will demonstrate foundational expertise in deep learning, reinforcement learning, and applied mathematics to help develop models capable of reasoning, planning, and acting across diverse modalities. This is a chance to define core algorithmic improvements for multimodal foundation models, scaling your ideas through our Nemotron Omni and VoiceChat platforms. You will work on high-impact, high-visibility large language models and multimodal AI products that improve the experience for millions of users. If you are creative and passionate about solving real-world agentic AI challenges, come join our Nemotron LLM team. For more details on Nemotron LLM, check What you’ll be doing: Apply fundamental and applied research to develop, train, fine-tune, and deploy large language models for agentic systems encompassing audio-visual reasoning, tool usage, and document understanding. Advance post-training and alignment methods including instruction tuning, preference optimization, and RLHF/RLVR/MOPD to improve multimodal agents for complex use cases. Research and develop agentic reasoning and grounded perception capabilities, focusing on planning, tool execution, and long-horizon task completion across digital and physical environments. Lead the collection, development, and benchmarking of multimodal datasets, ensuring high-quality evaluation of model accuracy, safety, and task completion success. What we need to see: Master’s degree (or equivalent experience) or PhD in Computer Science, AI, or Applied Math with 8+ years of relevant work experience. Excellent programming skills in Python with strong fundamentals in scalable model development and deep learning frameworks like PyTorch. Strong knowledge of ML/DL techniques and modern foundation model architectures, including Transformers and mixture-of-experts models. Foundational understanding of reinforcement learning algorithms and implementation, including MDPs, policies, and reward design. Hands-on experience in post-training multimodal models for omni-modality (audio-visual) reasoning, full-duplex voice chat, and human-AI interaction. Proven ability to manage model development life cycles, including dataset versioning, experiment tracking, and evaluation pipelines. Ways to stand out from the crowd: Strong record of publications in top-tier AI and machine learning venues such as NeurIPS, ICML, ICLR, or CVPR. Validated experience training and deploying multimodal foundation models using large-scale distributed infrastructure. Experience applying deep reinforcement learning techniques to train multimodal agents in complex simulation or gaming environments. Background in audio/speech AI, especially audio language models or audio generation. Background in building embodied AI systems that integrate multimodal perception with backend action-fulfillment and long-horizon planning. With highly competitive salaries and a comprehensive benefits package, NVIDIA is considered one of the industry’s most desirable employers. As you plan your future, see what we can offer you and your family at . If you are a creative and autonomous engineer with a genuine passion for state-of-the-art technology, we want to hear from you! Your base salar

NVIDIA被广泛认为是技术行业最令人向往的雇主之一。我们在高性能计算、人工智能和可视化领域处于领先地位。我们的核心发明——GPU，作为现代计算机的视觉皮层，为我们的整个产品系列提供动力。GPU深度学习点燃了现代AI时代——下一个伟大的计算时代——GPU充当着从机器人和自动驾驶汽车到对话式AI等一切事物的大脑。今天，我们在全球被称为“AI计算公司”。我们希望通过引入世界上最聪明的人才来壮大我们的团队。加入我们，站在技术进步的最前沿。

NVIDIA正在招聘高级深度学习科学家，以推进我们在流式传输和代理式多模态AI方面的工作。您将展示在深度学习、强化学习和应用数学方面的基础专业知识，帮助开发能够在多种模态之间进行推理、规划和行动的模型。这是一个为多模态基础模型定义核心算法改进的机会，通过我们的Nemotron Omni和VoiceChat平台扩展您的想法。您将致力于高影响力、高可见度的大型语言模型和多模态AI产品，改善数百万用户的体验。如果您富有创造力并热衷于解决现实世界的代理式AI挑战，欢迎加入我们的Nemotron LLM团队。有关Nemotron LLM的更多详情，请查看

您将要做的工作：

应用基础和应用研究来开发、训练、微调和部署用于代理式系统的大型语言模型，涵盖视听推理、工具使用和文档理解。

推进后训练和对齐方法，包括指令调优、偏好优化以及RLHF/RLVR/MOPD，以改进多模态代理应对复杂用例的能力。

研究和开发代理式推理与基于感知的能力，重点关注规划、工具执行以及在数字和物理环境中的长时程任务完成。

领导多模态数据集的收集、开发和基准测试，确保对模型准确性、安全性和任务完成成功率进行高质量评估。

我们需要看到的：

计算机科学、AI或应用数学硕士（或同等经验）或博士学位，具有8年以上相关工作经验。

出色的Python编程能力，具备可扩展模型开发和深度学习框架（如PyTorch）的扎实基础。

深入了解ML/DL技术和现代基础模型架构，包括Transformers和混合专家模型。

对强化学习算法及实现（包括MDP、策略和奖励设计）有基础性理解。

具有对多模态模型进行后训练的实践经验，涉及全模态（视听）推理、全双工语音聊天和人机交互。

具备管理模型开发生命周期的 proven 能力，包括数据集版本管理、实验跟踪和评估流水线。

脱颖而出的方式：

在顶级AI和机器学习会议（如NeurIPS、ICML、ICLR或CVPR）上有强有力的发表记录。

具有使用大规模分布式基础设施训练和部署多模态基础模型的验证经验。

具有应用深度强化学习技术在复杂仿真或游戏环境中训练多模态代理的经验。

具有音频/语音AI背景，尤其是音频语言模型或音频生成。

具有构建具身AI系统的背景，将多模态感知与后端动作执行和长时程规划相结合。

凭借极具竞争力的薪资和全面的福利待遇，NVIDIA被认为是行业中最令人向往的雇主之一。在规划您的未来时，请在我们的网站上了解我们能为他和您的家人提供什么。如果您是一位富有创造力且自主的工程师，对最先进的技术充满真正的热情，我们希望听到您的声音！您的基本薪资

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