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职位TikTok

Machine Learning Engineer, TikTok Search Local Services

TikTok

Machine Learning Engineer, TikTok Search Local Services

TikTok

Singapore

·

On-site

·

Full-time

·

2mo ago

福利待遇

Equity

Learning

Healthcare

Parental Leave

Remote Work

必备技能

Python

TensorFlow

Airflow

About Tik Tok

Tik Tok is the leading destination for short-form mobile video. At Tik Tok, our mission is to inspire creativity and bring joy. Tik Tok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Creation is the core of Tik Tok's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At Tik Tok, we create together and grow together. That's how we drive impact-for ourselves, our company, and the users we serve. Join us.

About the Team

Our Search Team enhances local services by improving user discovery of hospitality, dining, and leisure experiences while driving ecosystem growth. They leverage large-scale machine learning to refine search and recommendation systems, focusing on personalized relevance, CTR/CVR prediction, and optimized conversion efficiency for billions of users.

Responsibilities

  • Support the local video service business to enhance user discovery of life services such as hospitality, dining, and leisure
  • Improve the search experience in local services and promote ecosystem growth
  • Utilize large-scale machine learning techniques in search and recommendation scenarios with billions of users to improve user shopping experiences and enhance conversion efficiency
  • Design and implement local services search algorithms across the full stack, including: Query analysis, relevance, recall, coarse ranking, fine ranking, and blended ranking. Personalized behavior modeling for relevance computation; CTR (Click-Through Rate) prediction, CVR (Conversion Rate) prediction. Vector recall and value blending.

Qualifications

Minimum Qualifications

  • Excellent analytical and problem-solving skills
  • Strong foundation in machine learning and deep learning, with experience in: NLP (Natural Language Processing), Personalization
  • Exceptional coding skills with solid knowledge of data structures and algorithms
  • Proficiency in Linux development environments

Preferred Qualifications

  • Prior experience in search, recommendation, or advertisement algorithms
  • Familiarity with local life services and e-commerce businesses

Additional Information

Tik Tok will be prioritizing applicants who have a current right to work in Singapore, and do not require Tik Tok sponsorship of a visa.

Tik Tok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At Tik Tok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

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关于TikTok

TikTok

TikTok

Late Stage

A short-form video entertainment app and social network platform

10,001+

员工数

Los Angeles

总部位置

$220B

企业估值

评价

3.8

10条评价

工作生活平衡

2.8

薪酬

3.7

企业文化

4.1

职业发展

3.2

管理层

2.9

68%

推荐给朋友

优点

Great team dynamics and support

Innovative and creative culture

Good learning opportunities

缺点

Work-life balance challenges

Fast-paced and stressful environment

High expectations and tight deadlines

薪资范围

49个数据点

Mid/L4

Senior/L5

Mid/L4 · Applied AI Product Data Scientist

1份报告

$273,000

年薪总额

基本工资

$210,000

股票

-

奖金

-

$273,000

$273,000

面试经验

2次面试

难度

4.0

/ 5

时长

21-35周

体验

正面 0%

中性 0%

负面 100%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Behavioral Interview

5

Final Round

6

Offer

常见问题

Coding/Algorithm

Behavioral/STAR

Technical Knowledge

Culture Fit