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

TikTok

Seattle (WA)

On-site

USD 202,160 - 368,220

Full time

14 days+

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Job summary

TikTok invites a Senior Machine Learning Engineer to advance ETA prediction for ecommerce logistics in a Seattle-based role. You will build end‑to‑end models and analytics for the supply chain and logistics networks, leveraging deep learning and big data tools.

You will work with state‑of‑the‑art algorithms, spanning trajectory prediction, network design, and optimization, with impact on operations and customer experience.

Qualifications

  • Master’s or PhD in Computer Science, Engineering, Operations Research or related fields.
  • Strong data-structures and algorithms knowledge; excellent problem-solving ability and programming skills.
  • Experience in applied machine learning; familiar with algorithms such as Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, etc.
  • Experience with at least one Big Data tool (e.g., Hive, Spark, MapReduce) and at least one deep‑learning tool (e.g., TensorFlow, PyTorch).
  • Work experience in e‑commerce, supply chain, logistics, transportation or related fields is preferred.
  • Publications in top conferences (KDD, NeurIPS, WWW, SIGIR, WSDM, CIKM, ICLR, ICML, IJCAI, AAAI) are preferred.
  • 3+ years of experience in machine learning, operations research or big‑data analysis.

Responsibilities

  • Build deep learning and statistical models to provide end‑to‑end ETA prediction for e‑commerce logistics.
  • Use data mining tools to build logistics network knowledge graphs for situational awareness & early warning system.
  • Analyze and predict spatio‑temporal trajectory sequences of express packages using DL methods.
  • Build a service network design model for location selection of transshipment centers and last‑mile stations.
  • Extract direction of logistics operation optimization, cost reduction and service quality improvement.
  • Develop innovative and state‑of‑the‑art e‑commerce logistics models and algorithms.

Skills

Machine learning
Deep learning
Data structures
Algorithms
Programming

Education

Master’s/PhD in CS/Engineering/OR

Tools

Hive
Spark
MapReduce
TensorFlow
PyTorch

Job description

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

Location: Seattle

Employment Type: Regular

Job Code: E2885

Responsibilities
  • Build deep learning and statistical models to provide end‑to‑end ETA prediction for e‑commerce logistics; fine‑adjust ETA expression to consumers to improve click‑to‑order rate while balancing negative review indicators.
  • Use data mining tools to build logistics network knowledge graphs for situational awareness & early warning system for logistics fulfillment; enable operations to discover and address logistics network anomalies and improve logistics fulfillment quality with service providers.
  • Analyze and predict the spatio‑temporal trajectory sequence of express packages through deep learning, statistical inference and other algorithmic methods; use trajectory prediction to enhance ETA prediction accuracy and provide key sample features for other prediction tasks.
  • Build a service network design (SND) model for location selection of transshipment centers and last‑mile stations, based on expected increase in logistics order volume.
  • Extract direction of logistics operation optimization, cost reduction and service quality improvement through in‑depth understanding of supply‑chain and logistics scenarios.
  • Develop innovative and state‑of‑the‑art e‑commerce logistics models and algorithms.
Qualifications
  • Master’s or PhD in Computer Science, Engineering, Operations Research or related fields.
  • Strong data‑structures and algorithms knowledge; excellent problem‑solving ability and programming skills.
  • Experience in applied machine learning; familiar with algorithms such as Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, etc.
  • Experience with at least one Big Data tool (e.g., Hive, Spark, MapReduce) and at least one deep‑learning tool (e.g., TensorFlow, PyTorch).
  • Work experience in e‑commerce, supply chain, logistics, transportation or related fields is preferred.
  • Publications in top conferences (KDD, NeurIPS, WWW, SIGIR, WSDM, CIKM, ICLR, ICML, IJCAI, AAAI) are preferred.
  • 3+ years of experience in machine learning, operations research or big‑data analysis.
Job Information

The base salary range for this position in the selected city is $202,160 – $368,220 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 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.

Legal 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;
  3. Exercising sound judgment.
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