Graduate ML Engineer — Global E‑Commerce Growth

TikTok; Singapore; Sur place; SGD 65 000 - 105 000; Plein temps

Résumé du poste

TikTok is seeking a Machine Learning Engineer Graduate to join the User Growth team focusing on global e-commerce growth. You will work on promotion algorithms and real-time budget optimization that directly influence tens of millions of users and billions in GMV.

The role offers opportunities to tackle bold ideas, learn rapidly, and contribute to a joint optimization of content recommendation and subsidies. Applicants should be graduating in 2027 and can apply to two positions at most.

Qualifications

• Bachelor's or Master's in Computer Science, Mathematics, Statistics, Operations Research, or related field, with solid algorithms/data structures knowledge.
• Strong expertise in machine learning and deep learning for recommendation/advertising/marketing.

Responsabilités

• Model user demand elasticity across products and coupon values with optimization to maximize GMV and conversion rate.
• Design globally optimal budget allocation and pricing algorithms for large-scale budgets across billions of users and products.
• Integrate real-time voucher capabilities into recommendation pipelines across video, live, and marketplace to enable joint traffic+subsidy decisions.
• Research and productionize causal inference and AI technologies (Uplift Modeling, E2E Modeling, RL, LLMs, AI Agents) to improve user conversion.

Connaissances

Algorithms & data structures

ML/DL

Causal Inference/Uplift Modeling

Operations Research optimization

CTR/CVR estimation

Formation

Bachelor's or Master's in CS/Math/OR

Description du poste

TikTok is seeking a Machine Learning Engineer Graduate to join the User Growth team focusing on global e-commerce growth. You will work on promotion algorithms and real-time budget optimization that directly influence tens of millions of users and billions in GMV.

The role offers opportunities to tackle bold ideas, learn rapidly, and contribute to a joint optimization of content recommendation and subsidies. Applicants should be graduating in 2027 and can apply to two positions at most.