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SakinaWEI/README.md

👋欢迎来到我的GitHub主页!

我是Sakina,目前在 GLM-4 团队,正在寻找 TOP Talents 加入我们 ~ Join us! Top Talents for AGI, Global Hiring!!

About our team: Our world-leading AI team has developed the cutting-edge large language and multimodal models and built the high-precision billion-scale knowledge graphs, the combination of which uniquely empowers us to create a powerful data- and knowledge-driven cognitive engine towards AGI.

  • GLM-4 大模型算法科学家/工程师
  • CogVLM 多模态大模型算法科学家/工程师
  • CodeGeeX2 大模型算法 代码方向
  • AgentBench/AgentLM 大模型算法
  • TTS 语音算法
  • AI Infra GLM-platform,深度学习框架,推理加速,网络,K8S
  • AIGC AI-Native C端产品经理
  • 前后端,底层开发,ACM、NOI竞赛选手

关于 ChatGLM 关于大模型 AGI,有任何感兴趣的话题,欢迎交流~ 可以戳我详聊👇

LLM Research Scientist/Engineer

Responsibilities:

  • Design and deploy state-of-the-art NLP/Multimodal LLM

  • Research areas include, but are not limited to, efficient large language model architecture, multimodal learning, self-supervised representation learning, unified cross-task learning, dataset construction, RLHF, etc.

Qualifications:

  • PhD/Master in Computer Science, Artificial Intelligence, or a related field.

  • Solid research accumulation in natural language understanding, machine learning, deep learning, and multimodal domains.

  • Excellent large model research capabilities, with a preference for those who have published high-quality papers in top conferences such as NeurIPS, ICLR, ICML, ACL, EMNLP, CVPR, JMLR, etc.

  • Outstanding collaborative abilities, able to coordinate with platform, data, and other teams to complete systematic work, excellent direction planning and implementation capabilities.

ML System Research Scientist/Engineer

Responsibilities:

  • Lead the creation of next-generation, high-capacity LLM platforms.

  • Collaborate with software engineers to build platforms with cutting-edge models.

Qualifications:

  • PhD/Master in Computer Science, Artificial Intelligence, or a related field.

  • Have prior experience working with training and inference of large language models.

  • Have experience in High performance, large-scale ML systems, GPUs, Kubernetes, Pytorch, or OS internals

  • Proficiency in programming languages such as Python or C++ and a track record of working with deep learning frameworks (e.g., pytorch, deepspeed, etc.).

  • Strong understanding of distributed computing framework & performance tuning and verification for training/finetuning/inference.

  • Being familiar with PEFT or MoE is a plus.

如果您对我的项目或工作有任何疑问或建议,请随时与我联系😊~

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