招聘

Machine Learning Engineer Intern - TikTok Search Team - 2026 Start (PhD)
San Jose, CA
·
On-site
·
Full-time
·
2mo ago
福利待遇
•Learning
•Healthcare
•Remote Work
•Unlimited Pto
必备技能
Airflow
Python
SQL
Responsibilities
Team Introduction
Our Search Engineering Team is responsible for building and owning Tik Tok's search engine which can provide our users with the best search experience. In Tik Tok Search Team, you'll have the opportunity to build full-stack search engine system and combine information retrieval technology with modern machine learning methods from related fields such as NLP, CV, and recommender system. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.
We are looking for talented individuals to join us for an internship in 2026. PhD Internships at Tiktok aim to provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies.
PhD internships at Tiktok provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and development events, and collaboration with industry experts.
Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date).
Internship Opportunities
This internship provides students the opportunity to join one of our engineering teams where you will have the opportunity to:
Participate in the improvement of the search core algorithm, possible directions include:
- Content understanding: Applying the industry's cutting-edge NLP and CV technology and leveraging LLM to match the most relevant videos for each search query, and continuously improve the relevance of Tik Tok search.
- User Behavior Modeling: solving the recommendation problem in search, let Tik Tok search increase the ability of personalization on the basis of "relevant", and understand users better.
- Video understanding: comprehensive use of NLP, CV, as well as LLM for better video understanding from the perspective of the video itself and social network, improve authority, credibility, and usefulness of search results.
Qualifications
Minimum Qualifications
- Must be able to commit to a 12-week full-time work.
- Currently pursuing a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
- Proficient coding skills and strong algorithm & data structure basis.
- Effective communication and teamwork skills.
- Experience in one or more of the following areas: NLP, Ranking, Ads, search engine, recommender system, distributed system, and machine learning.
Preferred Qualifications
- Graduating December 2026 onwards with intent to return to degree-program after the completion of the internship.
- Demonstrated software engineering experience from previous internship, work experience, coding competitions, or publications.
- High levels of creativity and quick problem-solving capabilities.
Privacy Statement
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
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关于TikTok

TikTok
Late StageA 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
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