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

About the role

The Knowledge Graph team is responsible for the neural network of e-commerce, including categorizing products, influencers, and merchants, mining product information, and providing this data to the recommendation team. The team manages operations related to product tags and category attributes, determines product suitability (e.g., clothing vs. sports, target audience), conducts competitive research, analyzes top-performing items, and handles brand recognition. This team bridges various aspects of the business and collaborates closely with other teams.

As a graduate, you will have opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must commit to an onboarding date by the end of the year.

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 product managers, data scientists, and the product & operation team to craft forward-thinking product strategies and features.
• Craft intricate knowledge graphs, encompassing product/content insights and category/brand/SPU development.
• Architect knowledge maps detailing buyer and product connections.

Qualifications

Minimum Qualifications

• Completing or recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related discipline.
• Passion or exposure to 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.
• Hands-on experience or group projects in relevant technical scenarios (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.

Pay

The base salary range for this position is $162,000 - $387,600 annually. Compensation may vary based on qualifications, skills, competencies, experience, and location. Base pay is one part of the total package, which may include additional discretionary bonuses/incentives and restricted stock units.

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).