Machine Learning Engineer Graduate (E-Commerce Supply Chain & Logistics)- 2025 Start (Phd)

Responsibilities

Team Introduction:
Join the E-commerce Global Supply Chain and Logistics team at TikTok! We're enhancing the shopping experience and reducing logistics operational costs. We are seeking brilliant and motivated graduate software engineers, who are eager to apply their knowledge in machine learning (ML), operations research (OR), data mining, and statistical inference to real-world challenges.

We are looking for talented individuals to join our team in 2025. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.

We are looking for talented individuals to join our team in 2025. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.

Applications will be reviewed on a rolling basis. We encourage you to apply early.

Candidates can apply for a maximum of TWO positions and will be considered for jobs in the order you applied for. The application limit is applicable to TikTok and its affiliates globally.

Responsibilities:
1. Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
2. Utilize e-commerce big data and deep learning models to predict end-to-end estimated time of arrival (ETA), and some logistics events such as failed delivery, delivered but not received to enhance the user logistics experience. Build logistics network knowledge graphs and predict the spatio-temporal trajectory sequence of express packages through deep learning, statistical inference and other algorithmic methods. Use NLP and LLM algorithms to handle address problems such as address verification and address suggestion.
3. Utilize time series forecasting techniques to predict sales at different granularities and horizons, such as warehouse-level manpower forecasting, inventory-level demand forecasting etc. We need strong machine learning and deep learning skills to detect important factors and model the relationship between the future and history.
4. Participate in the growth of e-commerce merchants/creators, responsible for the growth algorithm of e-commerce merchants/creators, including potential merchants/creators mining algorithm, tiering algorithm, out-reach algorithm, growth algorithm, etc. Work closely with e-commerce merchants/creators related operations and product teams to achieve the high-quality growth goal of e-commerce merchants/creators.
5. Combined with massive e-commerce information, through data mining and machine learning, predict the performance of products in traffic/conversion, improve the efficiency of product operation strategy and pricing/subsidy strategy, and assist in optimizing traffic distribution, to satisfy the requirements of product growth, cost optimization and some other scenarios.

Qualifications

Minimum Qualifications:
- Master's or Phd degree in fields such as artificial intelligence, computer science, operations research, automation, statistics, mathematics, or related disciplines, with experience in data mining and deep learning.
- Proficient in machine learning and statistics, familiar with the principles and model structures of common machine learning and deep learning algorithms for classification, regression, and clustering, with practical application experience.
- Proficient in programming languages such as Python/Java, possessing excellent coding abilities, and familiar with at least one common machine learning/deep learning framework (TensorFlow/PyTorch etc.).
Demonstrates a spirit of exploration, outstanding data analysis capabilities, strong initiative, and excellent teamwork and communication skills.

Preferred Qualifications:
- Demonstrated software engineering experience from previous internship, work experience, coding competitions, or publications
- Internship experience or research experience, especially in e-commerce, supply chain, logistics, and transportation.
- Published papers at conferences such as KDD, NeurIPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RecSys, or having participated in data mining/machine learning competitions.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $136800 - $259200 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 may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.