Machine Learning Engineer Graduate (E-Commerce Supply Chain & Logistics) - 2026 Start (PhD)
TikTok
San Jose, CA, US
Onsite
2026-06-25
Announced salary
$156k–$317k
Low
$116K
Median
$153K
High
$202K
Market in San Jose · BLS OEWS 2025
Job description
Technology
Machine Learning Engineer Graduate (E\-Commerce Supply Chain \& Logistics) \- 2026 Start (PhD)
Location
:
San Jose
Employment Type
:
Regular
Job Code
:
A245110
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 2026\. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company.
Successful candidates must be able to commit to an onboarding date by end of year 2026\. Please state your availability and graduation date clearly in your resume.
**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 forecastin