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👇

• Email: [email protected]
• Wechat: SakinaWEI

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😊~