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

About the role

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, 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.

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 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.
• Categorize products, influencers, and merchants; mine product information and provide this data to the recommendation team.
• Manage operations related to product tags and category attributes.
• Determine product category suitability (e.g., clothing vs. sports) and target audience.
• Conduct competitive research to identify top‑performing items and analyze performance differences among similar products.
• Contribute to brand recognition efforts.

Qualifications

Minimum Qualifications: Individuals who are completing or have recently completed a Bachelor's 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.

Preferred Qualifications: Individuals who are completing or have recently completed a Master's degree in Software Development, Computer Science, Computer Engineering or a related discipline. 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. Any hands‑on experience or group projects in relevant technical scenarios will be a plus.

Benefits

• Day‑one access to medical, dental, and vision insurance.
• 401(k) savings plan with company match.
• Paid parental leave.
• Short‑term and long‑term disability coverage.
• Life insurance.
• Wellbeing benefits.
• 10 paid holidays per year.
• 10 paid sick days per year.
• 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
• Benefits may vary depending on the nature of employment and the country work location; the Company reserves the right to modify or change these benefits programs at any time, with or without notice.

Pay

The base salary range for this position in the selected city is $121,600 - $243,200 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.