Machine Learning Graduate (eCommerce Recommendation and Marketing) - 2026 Start (PhD)

About the Role

Key Responsibilities

• Build a full lifecycle user data and value system to address core pain points and business challenges in e-commerce user growth.
• Participate in developing an industry-leading online marketing inference algorithm engine that integrates signals from search, recommendation, and marketing, moving from isolated decision-making in each domain to joint decision-making across domains.
• Optimize international e-commerce user growth and intelligent marketing by improving the cost-effectiveness of key budget spending through algorithms — including subsidy distribution, product pricing, budget allocation, and traffic strategies — to enhance subsidy and traffic efficiency, ultimately driving GMV growth.

Requirements

• PhD degree or above, graduating in 2026, preferably in Artificial Intelligence, Machine Learning, Computer Science, Mathematics, Operations Research, or related fields with 0-1 year of work experience.
• Solid foundation in algorithms and data structures, with strong programming skills.
• Strong learning ability, curiosity, communication, and teamwork skills.
• Solid foundation in machine learning algorithms, familiar with one or more of the following: machine learning, deep learning, causal inference, reinforcement learning.

Nice to Have

• Publications in top AI conferences/journals, or strong performance in ACM / machine learning competitions.
• Research or project experience in user growth, intelligent marketing, or advertising; experience in LTV prediction, uplift modeling, operations research, sequence modeling, or multi-scenario modeling optimization.

Qualifications

• Doctoral degree (PhD) in a relevant field
• Graduating in 2026

Benefits & Perks

• Paid parental leave
• Paid holidays
• Disability insurance
• Health insurance
• Dental insurance
• RSU (Restricted Stock Units)
• Vision insurance
• 401(k) matching
• Life insurance
• Paid sick time
• Additional 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)