Machine Learning Engineer Intern (TikTok Search) - 2026 Start (PhD) San Jose PhD Intern- 2026 Start

Ellis Technologies, Inc.

San Jose (CA)

On-site

USD 68,000 - 97,000

Full time

14 days+

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Benefits offered by this job

Health insurance
Housing allowance
Paid holidays
Paid sick time

Job summary

TikTok in San Jose is offering a 12-week internship to contribute to the search core algorithm. You will work on improving relevance for video search, using NLP, CV and ML techniques, and model user behavior to enhance personalization.

The ideal candidate is pursuing a PhD in CS/CE, has strong coding skills, and can communicate effectively in a team. The role includes day‑one health coverage and a competitive hourly rate in a full‑time schedule.

Qualifications

  • Pursuing a PhD in software development or related technical field.
  • Strong programming ability and data‑structure knowledge.
  • Effective collaboration and communication in a team environment.

Responsibilities

  • Contribute to improving the search core algorithm and relevance for video search.
  • Model user behavior to enhance personalization and ranking in search results.
  • Leverage NLP, CV and ML techniques for video understanding and quality assessment.

Skills

Coding skills
Communication
Teamwork
NLP

Education

PhD student in CS/CE

Job description

Location: San Jose

Employment Type: Intern

Job Code: A117916

Responsibilities
  • Participate in the improvement of the search core algorithm, possible directions include:
    • Content understanding: Applying industry cutting‑edge NLP and CV technology and leveraging LLM to match the most relevant videos for each search query, and continuously improve relevance.
    • User behavior modeling: Solving the recommendation problem in search, increasing personalization on the basis of relevance and better understanding of users.
    • Video understanding: Comprehensive use of NLP, CV and LLM for better video understanding from the perspective of the video itself and the social network, improving authority, credibility, and usefulness of search results.
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.
  • Proficient coding skills and a 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
  • Demonstrated software engineering experience from previous internship, work experience, coding competitions, or publications.
  • High levels of creativity and quick problem‑solving capabilities.
Benefits
  • 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).
  • Interns who are not working 100% remote may also be eligible for housing allowance.
Job Information

The hourly rate range for this position in the selected city is $60 - $60.

Equal Employment Opportunity
  • 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.
  • The 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:
    • Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
    • Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
    • Exercising sound judgment.
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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