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FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI…
About the Team The Inference Infrastructure team is the creator and open-source maintainer of AIBrix, a Kubernetes-native control plane for large-scale LLM inference. We are part of ByteDance’s Core Compute…
1、负责抖音AI相关创新方向工具产品能力及用户产品能力建设； 2、探索基于直播、视频和社交的新的互动场景与AIGC/大模型的结合点，实现创新功能； 3、负责自研大模型训练框架的维护、优化与核心技术攻关； 4、深入理解主流大模型训练框架技术架构，持续跟踪行业前沿技术（如KVCache/DeepSpeed/FlashAttention等），优化训练推理效率。 1、本科及以上学历，计算机，软件，电信或相关专业；…
ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible…
ML/AI Research Engineer — Agentic AI Lab (Founding Team) Location: San Francisco Bay Area Type: Full-Time Compensation: Competitive salary + meaningful equity (founding tier) Backed by 8VC, we're building a…
AML-MLsys combines system engineering and the art of machine learning to develop and maintain massively distributed ML training and Inference system/services around the world, providing high-performance, highly…
About the Institute of Foundation Models We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI…
ML Ops Engineer — Agentic AI Lab (Founding Team) Location: San Francisco Bay Area Type: Full-Time Compensation: Competitive salary + meaningful equity (founding tier) Backed by 8VC, we're building a world-class…
1、深入探索剪映、即梦、醒图等产品的Agent应用，构建端到端的Agent评测体系，设计和研发领先的Agent模型与链路，推动AI技术在视频、图片创作领域中的突破； 2、建立并迭代Agent模型与链路与模型的评估体系，探索数据与模型的共进化反馈体系； 3、通过Prompt/Context Engineering、SFT、RLHF等算法提升Agent能力上限，实现Agent在视频/图片生成、编辑等能力上的全面提升；…
About Liquid AI Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory…
About Us: We are establishing the first distributed Al infrastructure dedicated to personalized Al. The evolving needs of a data-driven society are demanding scalability and flexibility. We believe that the future of…
1、负责超大规模机器学习系统架构的设计开发，解决系统高并发、高可靠性、高可扩展性等技术难关； 2、负责大模型分布式训练任务性能优化，涵盖LLM/MLLM模型的CPT/SFT/RL等训练系统的搭建和性能优化； 3、与算法部门深度合作，进行算法与系统的联合优化； 4、国产硬件的适配和性能优化。 1、优秀的代码能力、数据结构和基础算法功底，熟练掌握Linux环境下的C/C++，Python；…
We are thrilled to introduce you to our team at the Chief Data and Analytics Office (CDAO) organization. As the driving force behind the firm wide adoption of Artificial Intelligence (AI) across our company, our…
We are thrilled to introduce you to our team at the Chief Data and Analytics Office (CDAO) organization. As the driving force behind the firmwide adoption of artificial intelligence (AI) across our company, our…
1、端到端AI Factory架构设计：负责超大规模、高可用AI Factory的端到端架构设计与演进；主导面向万卡/十万卡级GPU/加速器集群的计算、高性能网络（RDMA/RoCE/1、6T/CPO）及低延迟存储系统的协同设计，支撑百亿/千亿参数大模型（LLM/VLM）的高效Pre-training和超大规模分布式Inference工作负载；…
在内容生成领域，音频生成逐渐成为热门研究方向，具有广阔的应用前景和研究价值。本课题专注于音频内容生成方向，包括但不限于： 1）音视频联合生成：探索如何使模型在生成过程中有效地结合文本、语音和图像信息，提升生成结果的相关性和自然度。 2）音频数据处理与融合：研究音频数据的预处理和特征提取技术，以优化生成模型的输入输出。 3）多模态生成模型的性能评估：设计自动化评估方法，量化多模态生成模型在下游任务中的表现。…
该课题聚焦于利用原生语音大模型构建情感陪伴 Agent，通过实时全双工交互，精准理解和感知用户情绪，凭借高情商为用户提供极具价值的回复，旨在为用户打造温暖、贴心且高度智能的情感陪伴体验。研究内容： 1）模型优化：参与优化原生语音多模态大模型，通过改进Speech Tokenizer和文本-语音的对齐机制等措施，提升模型对语音中包含的语义以及声学信息的实时理解与处理能力，增强其对用户情绪的精准识别。…
大语言模型（LLM）最近取得的突破极大地加速了多模态大语言模型（MLLM）的发展。全模态多模态大语言模型（Omni-MLLM）通过融入如视频、音频等额外的非语言模态，拓展了多模态大语言模型的能力，从而有助于更全面、多维度地理解各种模态，提供更强的智能以及更智能的交互模式。研究方向包括不限于： 1)…
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