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

Senior Machine Learning Engineer - TikTok E-commerce Global Supply Chain and Logistics at TikTok in Seattle, WA.

Responsibilities

The E-commerce Global Supply Chain and Logistics team is dedicated to enhancing clients' shopping experience and reducing logistics operational cost in TikTok E-commerce. We are currently looking for talented software engineers that have 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.

• Build deep learning and statistical models to provide end-to-end estimated time of arrival (ETA) prediction for the e-commerce logistics. Through fine adjustment of ETA expression to the consumers, improve the click-to-order rate while balancing the negative review indicators.
• Use data mining tools to build logistics network knowledge graphs, based on which to construct a situational awareness & early warning system for logistics fulfillment, enabling operations to discover and deal with logistics network anomalies, and to improve the logistics fulfillment quality together with logistics service providers.
• Analyze and predict the spatio-temporal trajectory sequence of express packages through deep learning, statistical inference and other algorithmic methods. This trajectory prediction can help to build a better understanding of logistics network dynamics, improve ETA prediction accuracy and provide important sample features for other prediction tasks.
• Build a service network design (SND) model for the location selection of transshipment centers and last mile stations based on an expected increase in logistics order volume.
• Extract the direction of logistics operation optimization, cost reduction and service quality improvement by in-depth understanding of supply chain and logistics scenarios.
• Develop innovative and state-of-the-art e-commerce logistics models and algorithms

Requirements

• Master's or PhD degree in Computer Science, Engineering, Operations Research or related fields.
• Strong in data structures and algorithms, with excellent problem-solving ability and programming skills
• Experience in applied machine learning, familiar with one or more algorithms such as Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks etc.
• Experience with at least one of the Big Data tools (For eg. Hive sql/Spark/Mapreduce; at least one of the Deep Learning tools(For eg. Tensorflow/Pytorch).

Preferred Qualifications

• Work experience in e-commerce, supply chain, logistics, transportation or related fields is preferred.
• 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.

Job Information

[For Pay Transparency] Compensation Description (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.

About the Company

The Global Business Solutions (GBS) team is responsible for the revenue growth of the TikTok business, and our teams include Sales, Marketing, Ops, Account Managers, Agency and partnerships, as well as Marketing Science.

At TikTok, our Global Business Solutions (GBS) team plays a key role in generating revenue by promoting our advertising solutions, onboarding new clients, driving ad campaigns, and more. As the TikTok community grows at an unprecedented speed around the world, our GBS team leads groundbreaking projects that are changing the landscape of the advertising industry in real time.

We're seeking an analytically driven, and detail-oriented Client Solutions Manager (CSM) Intern to join our Ecommerce Team. As a CSM, you will partner closely with Client Partners and Client Solutions Managers to drive revenue by identifying opportunities, leveraging data insights, and delivering consultative solutions for advertisers.

This role centers on client education, relationship growth, data analysis, and campaign success. You will provide strategic recommendations to both clients and internal teams, ensuring campaigns achieve business objectives while optimizing long-term partnerships. Success in this role requires strong data analytics skills, adaptability in a fast-paced environment, and a test-and-learn mindset to uncover the best solutions.

Additional Information

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.