LLM Software Engineer
Job Summary
Job Description
The company is seeking an LLM Software Engineer. The role involves designing and developing NLP services and applications. The engineer will provide natural language processing solutions for intelligent manufacturing, office management, and data mining and processing to reduce production line management costs and improve efficiency. The ideal candidate will have a strong background in computer science or related fields, excellent programming skills in Python, and proficiency in machine learning and deep learning algorithms, as well as common natural language processing methods. Experience with deploying algorithms, training models, fine-tuning pre-trained models, AutoML, and few-shot learning is also required. Strong communication and collaboration skills are essential, along with the ability to read literature and stay updated on cutting-edge technologies.
Must have:
- Strong programming skills in Python
- Excellent mathematical modeling skills
- Proficiency in machine learning and deep learning algorithms
- Familiarity with NLP methods
- Experience deploying algorithms and training models
- Strong communication and collaboration skills
- Experience with fine-tuning pre-trained models
Good to have:
- Experience with AutoML
- Experience with few-shot learning
- Ability to read literature and track cutting-edge technologies
2 skills required
Job Details
Company Description
Bosch China Innovation and Software Development Campus
博世创新与软件开发中心
博世创新软件开发（无锡）有限公司针对交通出行的电动化、自动化、互联化、个性化，提供面向未来的创新技术和前沿解决方案，加速针对中国市场的技术战略的实现和发展。博世软件中心主要发展方向包括智能网联汽车、智能座舱、自动驾驶、车路云协同、工业4.0、人工智能大数据、智能家居、嵌入式软件服务。博世中国创新与软件开发中心以软件为客户赋能，在汽车自动驾驶、氢燃料电池、重卡电驱动桥、多合一的控制器等多个领域取得创新研发成果。
Job Description
设计和开发基于NLP的服务和应用程序。
为智能制造、办公管理、数据挖掘和处理等提供自然语言处理解决方案，降低生产线管理成本，提高生产效率。
Qualifications
- 计算机科学、数学、统计学、语言学或相关专业教育背景。
- 较强的编程能力（Python）和优秀的数学建模能力。
- 熟练掌握常见的机器学习（感知器、决策树）、深度学习算法（CNN、RNN、Transformers）和常见的自然语言处理方法（TF-IDF、N-Gram、word2vec）。
- 部署算法和训练模型的经验。
- 较强的表达、沟通和协作能力。
- 具有预训练模型的微调经验以及AutoML和少镜头学习经验。
- 优秀的文献阅读能力，对前沿技术的跟踪意识。
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