我们正在寻找一位在训练生成式人工智能模型方面具有丰富经验的研究工程师。
作为我们研究团队的一员，您将在构建最先进的多模态基础模型和管理数千个GPU上的大规模训练运行方面发挥关键作用。您的专业知识将直接影响我们下一代人工智能技术的性能、可扩展性和效率。
主要职责
1.领导并促进多模态基础模型的突破性研究。
2.设计、开发和试验创新的算法、架构和技术，以增强模型性能和可扩展性。针对生产环境优化模型，重点关注计算效率、吞吐量和延迟，同时保持准确性和鲁棒性。
3.分析和管理大规模数据集群，识别训练管道和数据加载过程中的低效和瓶颈。
4.与跨职能团队合作，包括数据、应用研究和基础设施团队，以推动有影响力的项目。
职位要求：
1.较强的Python和PyTorch工程技能。拥有使用PyTorch从0开始构建机器学习模型的实践经验。
2.熟悉生成式多模态模型，如Diffusion Models和GANs。
3.对基本深度学习概念（包括Transformers）有扎实的理解。
优选经验：
1年以上工业界或学术界实验室研究经验。有处理涉及100+GPU的大型分布式系统的经验。精通Linux集群、系统和脚本。
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