Machine Learning Engineer - TikTok E-commerce Global Supply Chain and Logistics

$136,000 - $205,000/Yr

Tiktok - San Jose, CA

Full-time - Mid Level

San Jose, CA

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

TikTok is the leading destination for short-form mobile video, and our mission is to inspire creativity and bring joy. The E-commerce Global Supply Chain and Logistics team is dedicated to enhancing clients' shopping experience and reducing logistics operational costs in TikTok E-commerce. We are currently seeking talented software engineers with a deep understanding of machine learning (ML), operations research (OR), data mining, and statistical inference. This position can be fulfilled in our San Jose and Seattle offices. As a Machine Learning Engineer, you will be responsible for building deep learning and statistical models to provide end-to-end estimated time of arrival (ETA) predictions for e-commerce logistics. You will fine-tune ETA expressions to improve the click-to-order rate while balancing negative review indicators. Additionally, you will utilize data mining tools to construct logistics network knowledge graphs, which will enable the development of a situational awareness and early warning system for logistics fulfillment. This system will help operations discover and address logistics network anomalies, ultimately improving fulfillment quality in collaboration with logistics service providers. Your role will also involve analyzing and predicting the spatio-temporal trajectory sequences of express packages using deep learning, statistical inference, and other algorithmic methods. This trajectory prediction will enhance our understanding of logistics network dynamics, improve ETA prediction accuracy, and provide essential sample features for other prediction tasks. Furthermore, you will build a service network design (SND) model for selecting locations for transshipment centers and last-mile stations based on expected increases in logistics order volume. By deeply understanding supply chain and logistics scenarios, you will extract directions for optimizing logistics operations, reducing costs, and improving service quality. Finally, you will develop innovative and state-of-the-art e-commerce logistics models and algorithms.

Responsibilities

• Build deep learning and statistical models for ETA prediction in e-commerce logistics.
• Fine-tune ETA expressions to improve click-to-order rates and balance negative review indicators.
• Use data mining tools to create logistics network knowledge graphs for situational awareness and early warning systems.
• Analyze and predict spatio-temporal trajectory sequences of express packages using deep learning and statistical inference.
• Construct a service network design model for transshipment centers and last-mile stations based on logistics order volume.
• Identify optimization directions for logistics operations, cost reduction, and service quality improvement.
• Develop innovative e-commerce logistics models and algorithms.

Requirements

• Master's or PhD degree in Computer Science, Engineering, Operations Research, or related fields.
• Strong knowledge of data structures and algorithms with excellent problem-solving and programming skills.
• Experience in applied machine learning with familiarity in algorithms such as Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, and Deep Neural Networks.
• Experience with at least one Big Data tool (e.g., Hive SQL, Spark, MapReduce) and one Deep Learning tool (e.g., TensorFlow, PyTorch).

Nice-to-haves

• Work experience in e-commerce, supply chain, logistics, transportation, or related fields.
• Publications at KDD, NeurIPS, WWW, SIGIR, WSDM, CIKM, ICLR, ICML, IJCAI, AAAI, and related conferences.
• 3+ years of working experience in machine learning, operations research, or big data analysis.

Benefits

• 100% premium coverage for employee medical insurance, approximately 75% for dependents, and a Health Savings Account (HSA) with company match.
• Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans.
• 10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) and 10 paid sick days per year.
• 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability.
• Mental and emotional health benefits through EAP and Lyra.
• 401K company match, gym, and cellphone service reimbursements.