Machine Learning Engineer Graduate (TikTok-Data-Search-Basic Ranking) - 2027 Start (PhD)

About the role

Our Search Engineering Team is responsible for building and owning TikTok's search engine, providing users with the best search experience. In this role, you'll build a full-stack search engine system and combine information retrieval technology with modern machine learning methods from fields such as NLP, CV, and recommender systems. We embrace self-direction, intellectual curiosity, openness, and problem-solving.

As a PhD Graduate, you will pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must commit to an onboarding date by the end of the year.

Responsibilities

As part of this full-time role, you will:

• Participate in applied research and improvement of the search core algorithm, including:
  • Content understanding: Apply cutting-edge NLP and CV technology and leverage LLM to match the most relevant videos for each search query, continuously improving search relevance.
  • User Behavior Modeling: Solve recommendation problems in search to enhance personalization while maintaining relevance and better understanding users.
  • Video understanding: Use NLP, CV, and LLM for comprehensive video understanding from the perspective of the video itself and social networks to improve authority, credibility, and usefulness of search results.
  • Search research and evaluation: Develop new retrieval, ranking, relevance evaluation, query understanding, multimodal search, or LLM application methods and translate research ideas into scalable product improvements.

Requirements

• Currently pursuing or recently completed a PhD degree in Computer Science, Electrical Engineering, Machine Learning, Artificial Intelligence, Information Retrieval, Natural Language Processing, Data Mining, Statistics, or a related technical field.
• Must have graduated with an applicable degree before onboarding.
• Research or practical experience in one or more areas: search, information retrieval, ranking, recommendation systems, natural language processing, multimodal learning, large language models, data mining, or machine learning systems.
• Ability to establish authorization to work in the United States without sponsorship or immigration-related benefits.

Preferred Qualifications

• Publications, preprints, patents, open-source contributions, or research projects in search, recommendation, NLP, information retrieval, machine learning, or related areas.
• Experience with large-scale retrieval, ranking, model training, evaluation, online experimentation, distributed systems, or production ML systems.
• Familiarity with relevance evaluation, query understanding, semantic retrieval, vector search, LLM applications, or multimodal search.
• Ability to define ambiguous technical problems, compare solution paths, and communicate trade-offs clearly.
• Interest in applying research to improve search quality, user experience, and product impact at a global scale.

Pay

The base salary range for this position is $162,000 - $316,800 annually. Compensation may vary based on qualifications, skills, competencies, experience, and location. This role may also be eligible for additional discretionary bonuses, incentives, and restricted stock units.

Benefits

• Day-one access to medical, dental, and vision insurance.
• 401(k) savings plan with company match.
• Paid parental leave, short-term and long-term disability coverage, and life insurance.
• Wellbeing benefits.
• 10 paid holidays per year.
• 10 paid sick days per year.
• 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).