Machine Learning Engineer Intern (Lead Ads) - 2027 Summer San Jose Undergraduate​/Master Intern

Discover a career that energizes and excites you every day.

@2026 Tik Tok

Technology

Location:

San Jose

Employment Type:

Intern

Job Code:

A75581

Share this listing:

• The Lead Ads team empowers Tik Tok's global monetization (billion-dollar business) via efficiently delivering lead ads on Tik Tok. Our mission is to push the boundaries of large-scale ads delivery systems and lead the innovations of Tik Tok's personalized online advertising.
  
  We are looking for talented individuals to join us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth.
  
  Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals.
  
  Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted.
  
  Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.
  
  Responsibilities:
  
  - Participate in the development of a large-scale Ads system
  - Responsible for relevance model and strategy optimization, such as semantic matching models, active learning, text/photo/video multi-model, ranking strategy, etc
  - Participate in the development and iteration of Ads algorithms by using Machine Learning.
  
  - Work on NLP (Natural Language Processing) capability improvement and query understanding, such as query classification, seq2seq, NER (Named Entity Recognition), knowledge graph, bidword optimization, etc
  - Work on CTR/CVR model estimation accuracy, data analysis, modeling, feature engineering
  - Research and develop Ads pacing algorithms, ads traffic control, etc
  - Partner with product managers and product strategy & operation team to define product strategy and features

Minimum Qualifications:

- Currently pursuing a Bachelor's or above degree in Computer Science, Computer Engineering, or a related technical discipline.

- Solid programming skills, including but not limited to:
Go, C/C++, Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.

- Good analytical thinking capability. Have essential knowledge and skills in statistics.

- Good theoretical grounding in the machine and deep learning concepts and techniques (CNN/RNN/LSTM, etc.).

- Familiar with the architecture and implementation of at least one mainstream machine learning programming framework (Tensor Flow/PyTorch/MXNet), familiar with its architecture and implementation mechanism.

- Must be able to commit to a 12-week full-time work period during Summer 2027.

Preferred Qualifications:

- Ads system, recommendation, searching, ranking, etc.

The hourly rate range for this position in the selected city is $45- $45.

Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance.

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

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…