Machine Learning Engineer Graduate (Data-Global E-Commerce-Search) - 2027 Start

About the role

The Search E-Commerce team leads the development of TikTok's advanced search algorithm, which powers its global e-commerce platform. Using large-scale machine learning, NLP, CV, and multi-modal technologies, we build a world-class search engine to deliver the best e-commerce search experience to over a billion monthly TikTok users. Our mission is to create a world where "no reasonably priced product is difficult to sell."

This full-time Graduate role offers early-career engineers the opportunity to join one of our engineering teams and work on bold ideas, complex challenges, and limitless growth. Successful candidates must commit to an onboarding date by the end of the year.

Responsibilities

• Participate in improving the search core algorithm in one or more of these areas:
  • Content understanding: Apply cutting-edge NLP and CV technology, leverage LLMs to match the most relevant videos for each search query, and continuously improve search relevance.
  • User Behavior Modeling: Solve recommendation problems in search to enhance personalization while maintaining relevance, and deepen understanding of user needs.
  • Video understanding: Use NLP, CV, and LLMs to analyze videos from both content and social-network perspectives, improving 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.

Requirements

• 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.

All successful candidates must be able to establish authorization to work in the United States; the company does not provide sponsorship or immigration-related benefits for this position.

Pay

The base salary range for this position is $121,600 – $243,200 annually. Compensation may vary based on qualifications, skills, competencies, experience, and location. Base pay is one part of the total package, which may also include 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).

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 to achieve meaningful breakthroughs for ourselves, our company, and our users.