Machine Learning Engineer, Recommendations - USDS E-commerce Alliance

About the role

The e-commerce alliance team aims to serve merchants and creators in the e-commerce platform to meet merchants' business indicators and improve creators' creative efficiency. By cooperating with merchants and creators, we aim to provide high-quality content and a personalized shopping experience for TikTok users, create efficient shopping tools at seller centers, and promote cooperation between merchants and creators.

Responsibilities

• Build and design large-scale machine learning algorithms to model the real-time interests of creators to improve conversion efficiency
• Optimize TikTok's massive commodity relationship mining and ranking and recall of creators' product recommendations, and improve the overall GMV of the platform
• Use the large scale of data to deeply analyze the behavior of creators and merchants and build targeted algorithm strategies to empower creators and merchants, improve merchants' monetization efficiency, and boost industrial upgrading
• Support the rapid development of TikTok's e-commerce business, serve millions of merchants, explore more efficient business models, satisfy users with the best shopping experience, and promote healthy ecological development

Minimum Qualifications

• Bachelor's degree or higher in Computer Science or related fields
• Strong programming and problem-solving ability
• This role is open to graduates in applied machine learning, familiar with one or more of the algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep, GBDT, LTR, Word2vec, DIN, Deep&Wide
• Experience in Deep Learning Tools such as tensorflow/pytorch
• Experience with at least one programming language like C++/Python or equivalent

Preferred Qualifications

• Experience in recommendation system, search engine, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields
• Publications at KDD, NeurlPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS and related conferences/journals, or experience in data mining/machine learning competitions such as Kaggle/KDD-cup etc.

Pay

The base salary range for this position in the selected city is $129,960 - $246,240 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.

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)

Schedule

Fully in-person schedule up to 5 days a week.