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Source channel @olddriverGDstudy · Post #29 · Mar 17

搜索使用说明 #搜索指南 因为电报软件对中文搜索支持不好,大队特别对队内资源搜索进行了整理汇集,使用方法说明如下: 1.1 原理: 电报对中文搜索支持不佳,汉字只有在前后含有asic码字符的前提下可以被正确搜索出,如 _广州修车大队_ (“_”指代空格)、(广州修车大队);等形式可以搜索“广州修车大队”搜索出相关信息;搜索“广州”等未被asic码间隔的汉字无法正确显示。 为正确搜索,在编制频道资源时,对重要信息可以采取Hashtag的形式已方便搜索,即以"#"字符开头,接汉字,以“空格字符”结尾的形式,点击一个hashtag即可快速定位该频道或聊天群内所有相同标签,建议所有管理在编辑重要资料包括ls信息、广播台、学习频道时正确使用hashtag。 !!注意标签不要随意编写,要参考搜索指南中有的标签类型!! 1.2 JS资源定位: JS目前支持 Hasgtag(#K老师)、数字标签(#GZ003)的搜索方式,在对应榜单和报告区中试用上述方式均可查找到JS的相关信息。 使用举例:在“广州公开榜”或“广州修车大队”的搜索栏中输入 #K老师 或 #GZ003,均可定位到K老师资料页;在报告区的搜索栏中输入#K老师 或 #GZ003,均可定位到K老师的验证报告。这两者是快速了解JS基本信息和评价的便捷办法。 1.3 标签查找 公榜榜单目前均支持标签查找,可以快速定位某种类型或地区的所有JS,目前仅支持Hashtag查找,目前常用标签解释如下: 地区标签: 一定要使用一级标签,例如 #天河区(注意不要有错别字) #颜值: 不解释 #服务: 评价中92、95的,有场子出身花式水平的,均会归入此类; #大胸: 不解释,一般D以上归入此类; #长腿: 不解释,一般168以上归入此类; #身材: 不解释,较为宽松; #嫩妹: 22岁以下或者长相很嫩的,白小纯的,loli系的,cos系的归入此类; #熟女: 30岁以上风韵犹存的,归入此类; #特服: 提供3p、3t、wt、字母等特殊服务的JS归入此类。 使用举例:在红榜的搜索栏中输入 #长腿,可以快速查看“莉贝伦”等8位长腿JS。 类型标签评价目前非常主观,有不妥之处请队内私信 JackJack 或其他管理人员修改。 1.4 资料查找 目前学习频道中试用hashtag来快速定位资料,目前使用的标签有如下几种: #安全CJ#素质CJ#卫生CJ #搜索指南 #大队玩法 #语录#秀哥语录 #技巧#知识

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Data Science Jobs

@datasciencejobs · Post #3203 · 03/30/2026, 12:04 PM

#vacancy#вакансия#job#работа#Data_Scientist#DS Senior Data Scientist 📍 Location: Serbia, Armenia (We are ready to discuss other countries as well) 🏢 Remote work is possible 💶 Payment terms are open to discussion from 3500 € and up About the product At FlameTree, we are building a platform for creating AI agents that help businesses scale customer support, lead follow-up, and sales across multiple communication channels — both inbound and outbound. Our AI agents work with knowledge bases, communicate in real time, and drive conversions across messaging platforms. The platform supports 150+ languages and integrates with WhatsApp, email, and web applications, offering strong security and high scalability for business growth. 🎯Responsibilities: • Design and develop the core agent layer responsible for orchestrating interactions with LLMs • Build and maintain complex conversational logic: state machines, agent workflows, and orchestration pipelines • Control and shape LLM behavior: prompt design, structured outputs, deterministic flows • Manage conversational context: memory, history, token limits, and degradation strategies • Ensure reliability and predictability on top of inherently non-deterministic models • Implement resilient integrations with LLM providers (timeouts, retries, fallbacks, multi-provider strategies) • Optimize latency and cost (streaming, batching, caching, token efficiency) • Debug complex production issues (inconsistent outputs, race conditions, state loss) • Contribute to system architecture: clear boundaries between agents, backend, and real-time components • Build observability around LLM pipelines (prompt/response logging, tracing, quality metrics) 🎯Requirements: • 5+ years of backend development experience with strong Python skills (async, architecture, performance) • Proven production experience with LLMs (not side projects): understanding of limitations, cost, and behavior • Experience building agent-based systems or complex orchestration logic (state machines, pipelines) • Ability to make LLM behavior predictable (structured outputs, schema validation, guardrails) • Strong debugging skills in non-deterministic systems • Deep understanding of API integrations (timeouts, retries, idempotency, backpressure) • Experience optimizing latency and throughput in production systems • Solid Docker experience and understanding of production environments • Ability to make architectural decisions independently and take ownership • Strong engineering mindset: writing maintainable, scalable, production-grade code 🎯Nice to Have: • Experience with multi-agent systems, tool/function calling • Experience with local LLMs (Ollama, vLLM, GPU inference) • Experience with real-time / voice systems • LLM observability (prompt tracing, evals, quality metrics) • Cost optimization at scale for LLM usage 🎯What Makes This Role Interesting: • You will work on the core intelligence layer of the product — not just integrations • Real production challenges: high load, low latency, reliability requirements • Direct impact on system architecture and technical decisions • Fast execution cycle — minimal bureaucracy • Engineering-driven approach to LLMs (reliability, control, metrics — not just prompt tinkering) • Strong engineering team focused on building real systems, not prototypes 🎯Who This Role Is NOT For: • Candidates without real production experience with LLMs • Engineers relying only on frameworks without understanding underlying mechanics • Developers without experience in high-load or latency-sensitive systems • People focused on quick hacks rather than building reliable systems 📩 If you want to join a team where everything is fast, exciting, and truly about AI — drop a message: https://t.me/Irene_Bakaeva!

Data Science Jobs

@datasciencejobs · Post #1327 · 02/16/2023, 08:01 AM

#vacancy#parttime#Data_Scientist#Python#NLP Мы ищем академического директора для магистерской программы Искусственный интеллект в области лингвистики (компьютерная лингвистика), реализуемой совместно с Томским государственным университетом. Каким мы видим идеального кандидата? - Senior Data Scientist в области NLP (Natural Language Processing) и выше с опытом работы в этом грейде от 5 лет; - Опыт в найме junior и middle-специалистов; - Понимание стандартов профессии и актуального профиля компетенций специалиста, требуемого на рынке труда; - Опыт работы в компаниях, лидирующих на российском или зарубежном рынке в выбранной индустрии; - Активный участник сообщества, опыт выступления на конференциях, митапах (или их организация) будет преимуществом. Предлагаем: - Удаленная парт-тайм работа до 20 часов в месяц. - Возможность реализовывать свои идеи и влиять на IT-индустрию/ - Ежемесячный гонорар, привязанный к количеству новых студентов (по типу роялти). - Крутая команда с сильной экспертизой в сфере EdTech. - Укрепление вашего личного бренда. - Бесплатное обучение на любом курсе образовательной группы SkillFactory: в школе дата-профессий и программирования SkillFactory, школе дизайна Contented. С полным ТЗ можно ознакомиться по ссылке- https://docs.google.com/document/d/11yE4ycHg_oZLRmfRD936yhVISWmtw3A1chxWUI-qe0Q/edit?usp=sharing Контакт для связи- @anika_kor

GitHub Trends

@githubtrending · Post #15438 · 01/26/2026, 11:30 AM

#python#agents#ai#ai_engineer#ai_engineering#copilot#data_science#data_scientist#generative_ai#gpt#machine_learning#ml_engineer#ml_engineering#openai AI Data Science Team is a free Python library with AI agents that speed up your data work 10X by handling loading, cleaning, visualization, EDA, feature engineering, modeling, and SQL tasks. Its flagship AI Pipeline Studio app creates visual, reproducible pipelines you can run with Streamlit after easy install (Python 3.10+, OpenAI or Ollama). This saves you hours on repetitive jobs, boosts accuracy, and lets you focus on insights and business results. https://github.com/business-science/ai-data-science-team