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

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 have the opportunity to 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 a culture of self-direction, intellectual curiosity, openness, and problem-solving.

As a 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 a full-time Graduate Engineer, you will:

• Participate in improving the search core algorithm in areas such as:
  • 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 better understanding users.
  • Video understanding: Use NLP, CV, and LLMs for deeper video analysis from both video and social network perspectives 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 immigration-related benefits for this position.

Pay

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

Benefits may vary depending on employment type and work location. The Company reserves the right to modify or change these benefits programs at any time.

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. Every challenge is an opportunity to learn and innovate as one team. We embrace an "Always Day 1" mindset, achieving meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless.