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机器学习工程师 - TikTok-数据-搜索-基础排序

雇主

TikTok

地点

California · San Jose · 美国

待遇

$面议

工作模式

线下

截止日期

1月8日

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岗位摘要

Develop and apply cutting-edge machine learning technologies in real-time large-scale systems to imp

岗位职责

About the Team
On the TikTok Search Team, you will have the opportunity to develop and apply cutting edge machine learning technologies in real-time large-scale systems, which serve billions of search requests every day.
Via advanced NLP and multi-modal models, our projects impact and improve the search experience for hundreds of millions of users globally.
We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.
Responsibilities
- Participate in the improvement of the search core algorithm, possible directions include: - Content understanding/matching: Applying the industry's cutting-edge NLP and CV technology to match the most relevant videos for each search query, and continuously improve the relevance of TikTok search.
- User Behavior Modeling: solving the recommendation problem in search, let TikTok search increase the ability of personalization on the basis of "relevant", and understand users better.
- Video understanding: comprehensive use of NLP, CV, and other technologies for better video understanding from the perspective of the video itself and social network, improve the authority, credibility, and usefulness of search results.

申请条件

Minimum Qualifications:
- Bachelor or advanced degree in computer science or a related technical discipline.
- Effective communication and teamwork skills.
- Proficient coding skills and strong algorithm & data structure basis.
Preferred Qualifications:
- Experience in one or more of the following areas is preferred: NLP, Ranking, Ads, search engine, recommender system, distributed system, and machine learning.

雇主简介

TikTok is a leading short-form video platform that develops core training and serving infrastructure for large-scale recommendation systems and AI infrastructure for foundation models and LLMs.

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数据来源:TikTok

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