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

About the role

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

This full-time Graduate role provides early-career engineers the opportunity to join one of our engineering teams, where you will:

Responsibilities

• Participate in the 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 the relevance of TikTok search.
  • User Behavior Modeling: Solve the recommendation problem in search to enhance personalization while maintaining relevance, and better understand users.
  • Video understanding: Use NLP, CV, and LLM for comprehensive video understanding from the perspective of the video itself and social networks to improve the authority, credibility, and usefulness of search results.
  • Search systems engineering: Design, build, test, and maintain search services, data pipelines, tools, or platform components that support search quality, reliability, latency, and user experience.

Qualifications

Minimum Qualifications

• Completing or recently completed a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science, Statistics, Mathematics, or a related technical discipline.
• Experience with at least one programming language such as Python, Java, C++, Go, or JavaScript through coursework, internships, projects, or equivalent practical experience.

Preferred Qualifications

• Experience with search, recommendation, machine learning, information retrieval, natural language processing, ranking, data mining, or backend systems.
• Familiarity with distributed systems, databases, data pipelines, online experimentation, or large-scale service development.
• Experience using data or metrics to debug, evaluate, or improve a product or system.
• Strong problem-solving, communication, and collaboration skills.
• Interest in building Search products and systems for a large-scale consumer platform.

As a condition of employment, all successful candidates must be able to establish authorization to work in the United States. The Company does not provide sponsorship or any immigration-related benefits for this position.

Pay

The base salary range for this position is $128,000 - $256,000 annually. Compensation may vary outside of this range depending on qualifications, skills, competencies, experience, and location. Base pay is one part of the total package, which may include 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.
• 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).

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

About TikTok

TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, with additional offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

At TikTok, we create value for our communities, inspire creativity, and bring joy. We lead with curiosity, humility, and a desire to make an impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We embrace an "Always Day 1" mindset, constantly iterating to achieve meaningful breakthroughs for ourselves, our company, and our users.