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職位描述 崗位職責(zé)： 1. 大語言模型本地化部署，建立公司的大語言本地模型，導(dǎo)入公司內(nèi)的知識庫。 2. 深入理解公司業(yè)務(wù)，負責(zé)AI產(chǎn)品應(yīng)用的需求分析、產(chǎn)品設(shè)計、架構(gòu)設(shè)計與開發(fā)。 3. 應(yīng)用AI算法或模型，設(shè)計并實現(xiàn)AI應(yīng)用。 4. 負責(zé)AI產(chǎn)品應(yīng)用的核心功能模塊開發(fā)，不限于數(shù)據(jù)處理、算法集成、模型訓(xùn)練與部署的后端支持等工作。 5. 負責(zé)設(shè)計和開發(fā)基于大模型的AI應(yīng)用平臺，包括但不限于文本對話(類 GPT)、信息搜索，圖文生成，負責(zé)包括不限于模型預(yù)訓(xùn)練、微調(diào)、部署以及支持下游應(yīng)用任務(wù)的持續(xù)優(yōu)化等。 6. 構(gòu)建基于大模型應(yīng)用的知識庫，包括但不限于知識建模、知識抽取、知識推理等；文本語料預(yù)處理、清洗、濾毒、標注、合成、多模態(tài)數(shù)據(jù)合成等。 7. 跟蹤行業(yè)動態(tài)，及時把握最新的AI技術(shù)以及應(yīng)用，為公司提供技術(shù)創(chuàng)新建議。 任職資格/崗位要求： 1. 計算機科學(xué)、人工智能、數(shù)據(jù)科學(xué)、電子工程、數(shù)學(xué)或相關(guān)領(lǐng)域的本科或碩士學(xué)位。 2. 具備大模型應(yīng)用實踐經(jīng)驗，熟悉市面上主流文本、多模型模型的特性，可以根據(jù)場景和需求，選擇不同的模型進行使用。 熟練掌握python/java等常見編程語言，熟練掌握各種AI框架，如Pytorch、Tensorflow等，熟練使用機器學(xué)習(xí)、深度學(xué)習(xí)算法。 3. 熟悉數(shù)據(jù)庫設(shè)計與開發(fā)，掌握關(guān)系型數(shù)據(jù)庫(如 MySQL、Oracle等)和非關(guān)系型數(shù)據(jù)庫(如 MongoDB、Redis等)的使用。 4. 了解分布式計算和模型部署技術(shù)（如 Kubernetes、Docker等） 5. 對新技術(shù)有強烈的學(xué)習(xí)欲望，具備快速學(xué)習(xí)能力，能夠持續(xù)關(guān)注和掌握最新的AI技術(shù)和應(yīng)用。 Job Responsibilities: 1. Establish the company's Deepseek large language local model and build an internal knowledge base within the company. 2. Gain an in-depth understanding of the company's business and take charge of requirements analysis, product design, architecture design, and development of AI product applications. 3. Apply AI algorithms or models to design and implement AI applications, including but not limited to Natural Language Processing (NLP), Computer Vision (CV), intelligent optimization, and prediction. 4. Develop core functional modules for AI product applications, including but not limited to data processing, algorithm integration, model training, and backend support for deployment. 5. Design and develop AI application platforms based on large language models, including but not limited to text dialogue systems (similar to GPT), information retrieval, image-text generation, and tasks such as model pretraining, fine-tuning, deployment, and continual optimization for downstream applications. 6. Build knowledge bases for applications of large language models, covering knowledge modeling, extraction, reasoning, text corpus preprocessing, cleaning, filtering, annotation, synthesis, and multimodal data synthesis. 7. Monitor industry trends, stay updated on the latest AI technologies and applications, and provide innovative technical suggestions to the company. Qualifications/Job Requirements: 1. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Electronic Engineering, Mathematics, or a related field. 2. Hands-on experience with large model applications, familiarity with mainstream text and multimodal models, and the ability to choose different models according to scenarios and requirements. o Proficient in common programming languages such as Python and Java. o Skilled in using various AI frameworks like PyTorch and TensorFlow. o Familiarity with machine learning and deep learning algorithms. 3. Proficient in database design and development, with knowledge of relational databases (e.g., MySQL, Oracle) and NoSQL databases (e.g., MongoDB, Redis). 4. Understanding of distributed computing and model deployment technologies (e.g., Kubernetes, Docker). 5. A strong desire to learn new technologies, with the ability to quickly acquire and continuously master the latest AI technologies and applications.