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トレンド企業

トレンド企業

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求人TikTok

Machine Learning Engineer Graduate (TikTok Shop Global E-Commerce, Recommendation) - 2026 Start (PhD)

TikTok

Machine Learning Engineer Graduate (TikTok Shop Global E-Commerce, Recommendation) - 2026 Start (PhD)

TikTok

Singapore

·

On-site

·

Full-time

·

2mo ago

福利厚生

Equity

Healthcare

必須スキル

Apache Spark

Airflow

SQL

Team Introduction

E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on Tik Tok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. We are a group of applied machine learning engineers and data scientists that focus on E-commerce recommendations. We are developing innovative algorithms and techniques to improve user engagement and satisfaction, converting creative ideas into business-impacting solutions. We are interested and excited in applying large scale machine learning to solve various real-world problems in E-commerce.

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 Tik Tok.

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.

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to Tik Tok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities

  • Participate in building large-scale (10 million to 100 million) e-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc in Tik Tok.
  • Build long and short term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently.
  • Design, develop, evaluate and iterate on predictive models for candidate generation and ranking (eg. Click Through Rate and Conversion Rate prediction), including, but not limited to building real-time data pipelines, feature engineering, model optimization and innovation.
  • Design and build supporting/debugging tools as needed.
  • Support the production of scalable and optimised AI/machine learning (ML) models.
  • Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models.
  • Run experiments to test the performance of deployed models, and identifies and resolves bugs that arise in the process.
  • Work in a team setting and apply knowledge in statistics, scripting and programming languages required by the firm.
  • Work with the relevant software platforms in which the models are deployed.

Minimum Qualifications

  • Final year or recent PhD graduate with a background in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
  • Strong programming and problem-solving ability.
  • Experience in applied machine learning, familiar with one or more of the algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep etc.
  • Experience in Deep Learning Tools such as tensorflow/pytorch.
  • Experience with at least one programming language like C++/Python or equivalent.

Preferred Qualifications

  • Experience in recommendation system, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields.
  • Publications at KDD, NeurlPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS and related conferences/journals, or experience in data mining/machine learning competitions such as Kaggle/KDD-cup etc.

Additional Information

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

If you have any questions, please reach out to us at apac-earlycareers@tiktok.com

連絡先と所在地

総閲覧数

2

応募クリック数

0

模擬応募者数

0

スクラップ

0

TikTokについて

TikTok

TikTok

Late Stage

A short-form video entertainment app and social network platform

10,001+

従業員数

Los Angeles

本社所在地

$220B

企業価値

レビュー

3.8

10件のレビュー

ワークライフバランス

2.8

報酬

3.7

企業文化

4.1

キャリア

3.2

経営陣

2.9

68%

友人に勧める

良い点

Great team dynamics and support

Innovative and creative culture

Good learning opportunities

改善点

Work-life balance challenges

Fast-paced and stressful environment

High expectations and tight deadlines

給与レンジ

49件のデータ

Mid/L4

Senior/L5

Mid/L4 · Applied AI Product Data Scientist

1件のレポート

$273,000

年収総額

基本給

$210,000

ストック

-

ボーナス

-

$273,000

$273,000

面接体験

2件の面接

難易度

4.0

/ 5

期間

21-35週間

体験

ポジティブ 0%

普通 0%

ネガティブ 100%

面接プロセス

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Behavioral Interview

5

Final Round

6

Offer

よくある質問

Coding/Algorithm

Behavioral/STAR

Technical Knowledge

Culture Fit