Machine Learning Engineer Graduate (E-Commerce Knowledge Graph) - 2027 Start (PhD)

The Knowledge Graph team is responsible for the neural network of e-commerce, which includes tasks such as categorizing products, influencers, and merchants, mining product information, and providing this data to the recommendation team. Additionally, they manage operations related to product tags and category attributes. When we come across a product, they determine whether it belongs to the clothing or sports category, who the product will be suitable for, etc. Furthermore, the team conducts competitive research, identifying top-performing items on the platform and analyzing why one similar product outperforms others. They are also involved in brand recognition. This team plays a pivotal role, in bridging various aspects of our business and maintaining close collaboration with other teams.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.

Responsibilities: - Dive deep into the construction and development of vast knowledge graphs that encapsulate real-world products, aiding in feed ranking, recommendations, and ads. - Collaborate closely with our dedicated product managers, astute data scientists, and the strategic product & operation team to craft forward-thinking product strategies and features. - Craft intricate knowledge graphs, encompassing areas like product/content insights and category/brand/SPU development. - Architect knowledge maps detailing buyer and product connections.

Minimum Qualifications: - Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering or a related discipline. - Passion or exposure to areas like machine learning, NLP (Natural Language Processing), multimodal systems, and computer vision. - Familiarity with or coursework related to programming languages like C++, Python, Go, or Java. - Strong teamwork and communication skills. Any hands-on experience or group projects in relevant technical scenarios will be a plus

Preferred Qualifications: - Familiarity with deep learning frameworks like TensorFlow/PyTorch. - Coursework or projects related to text classification, text matching, sequence labeling, and knowledge graphs. - Knowledge of domain adaptation, text mining, and unsupervised/semi-supervised methodologies. - Experience with machine learning and deep learning algorithms, and text representation methods. - Exposure to large-scale text data processing or tools like Hadoop/Spark/Hive/Flink.