About the team
Our team is responsible for developing cutting-edge NLP / ML algorithms and strategies to improve user consumption experience, inspire merchants' service quality and revenue, and build a fair and flourishing ecosystem on our E-commerce Platform.
More specifically, our team is responsible for the algorithms of Intelligent Customer Service under TikTok's global e-commerce business.
What you will do : - Building next-generation AI customer services using LLMs within the TikTok e-commerce ecosystem to better serve our customers.
Collaborate with product managers, data scientists, and the product strategy & operation team to define product strategies and features.
Responsibilities : 1. Applying LLMs for a variety of multilingual and multimodal scenarios of e-commerce business.2. Establishing a generative-based AI chatbot that is capable of resolving post-sale issues and achieving pre-sale interactive consultations.
3. Text generation, including product titles and descriptions, dialogue summary, auto-replying of emails and tickets, etc.
4. Machine translation, including optimizing translation quality in dozens of scenarios and language pairs in the e-commerce scenarios, as well as the research of related cutting-edge technologies.
In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager / department.
We regularly review our hybrid work model, and the specific requirements may change at any time.
Minimum Qualifications :
- Bachelor's degree in Computer Science or related technical field
- 3+ working experience in one of the following fields : machine learning, NLP, and computer vision
- Experience with software development in at least one of the following programming languages : C++, Python, Go, Java Preferred Qualifications : - Experience in NLP and LLM technologies.-
- Good sense of teamwork and communication skills, practical experience in relevant business scenarios is preferred.- Proficient in using at least one mainstream deep learning framework such as TensorFlow / PyTorch, understanding distributed training, distillation acceleration, and other implementation methods.
- Aware of certain processing methods and optimization experience on domain adaptation, small sample construction, text mining, unsupervised / semi-supervised, and other similar issues.
- Familiar with commonly used machine learning and deep learning algorithms, understand basic network model structure (DNN / LSTM / CNN, and text representation methods (LDA / Word2Vec / ELMo / GPT / BERT, , have practical experience in deep learning training and reasoning model tuning.
- Experience in large-scale text data processing or cleaning (Such as using Hadoop / Spark / Hive / Flink).
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