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崗位職責(zé)：
1. 跟蹤和研究最新的后端開(kāi)發(fā)技術(shù)和AI相關(guān)技術(shù)趨勢(shì)，積極探索如何將新技術(shù)應(yīng)用于公司的AI產(chǎn)品開(kāi)發(fā)。
2. 深入理解公司業(yè)務(wù)，負(fù)責(zé)AI產(chǎn)品應(yīng)用的需求分析、產(chǎn)品設(shè)計(jì)、架構(gòu)設(shè)計(jì)與開(kāi)發(fā)。
3. 應(yīng)用AI算法或模型，設(shè)計(jì)并實(shí)現(xiàn)AI應(yīng)用，包括但不限于自然語(yǔ)言處理 (NLP)、計(jì)算機(jī)視覺(jué) (CV)、智能優(yōu)化與預(yù)測(cè)等。
4. 負(fù)責(zé)AI產(chǎn)品應(yīng)用的核心功能模塊開(kāi)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(fù)責(zé)設(shè)計(jì)和開(kāi)發(fā)基于大模型的AI應(yīng)用平臺(tái)，包括但不限于文本對(duì)話(huà)(類(lèi) GPT)、信息搜索，圖文生成，負(fù)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(shí)庫(kù)，包括但不限于知識(shí)建模、知識(shí)抽取、知識(shí)推理等；文本語(yǔ)料預(yù)處理、清洗、濾毒、標(biāo)注、合成、多模態(tài)數(shù)據(jù)合成等。
7. 跟蹤行業(yè)動(dòng)態(tài)，及時(shí)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(jì)算機(jī)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(shí)踐經(jīng)驗(yàn)，熟悉市面上主流文本、多模型模型的特性，可以根據(jù)場(chǎng)景和需求，選擇不同的模型進(jìn)行使用。
熟練掌握python/java等常見(jiàn)編程語(yǔ)言，熟練掌握各種AI框架，如Pytorch、Tensorflow等，熟練使用機(jī)器學(xué)習(xí)、深度學(xué)習(xí)算法。
3. 熟悉數(shù)據(jù)庫(kù)設(shè)計(jì)與開(kāi)發(fā)，掌握關(guān)系型數(shù)據(jù)庫(kù)(如 MySQL、Oracle等)和非關(guān)系型數(shù)據(jù)庫(kù)(如 MongoDB、Redis等)的使用。
4. 了解分布式計(jì)算和模型部署技術(shù)（如 Kubernetes、Docker等）
5. 對(duì)新技術(shù)有強(qiáng)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. Track and research the latest backend development technologies and AI-related trends, actively exploring how to apply new technologies to the company's AI product development.
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.