Machine Learning Engineer Graduate (Monetization Technology - Ads Core Global) - 2027 Start

About the role

The TikTok Ads Core ML Team is focused on creating automatic delivery products for the next generation of advertising, developing it as a global business rather than just a monetization tool. We aim to consolidate the delivery funnel framework, enabling multiple teams to iterate in parallel. Our goal is to establish a world-leading ranking model and framework that benefits collaborators, users, and customers by improving returns.

As a graduate joining our team, you will have the opportunity to 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

• Assist in optimizing efficiency across the entire advertising funnel, including Recall & Rough-sort, Fine-sort (CTR/CVR), format/creative personalization, and system resource allocation.
• Research and develop a global advanced advertising delivery system using frontier technologies such as ML/DL, RL, LLM, and scaling laws in ads recommendation.
• Design and set up system frameworks and standards to continuously improve overall efficiency and meet diverse vertical business needs.
• Collaborate with product and business teams across various scenarios with global impact.

Requirements

Minimum Qualifications

• Completing or recently completed a Bachelor’s/Master’s degree in Computer Science, Mathematics, Statistics, or a related discipline.
• Solid programming skills, proficient in C/C++ and Python.
• Familiar with basic data structures and algorithms.
• Familiar with the Linux development environment.
• Strong analytical thinking capability.
• Essential knowledge and skills in statistics.
• Good theoretical grounding in deep learning concepts and techniques.
• Familiar with the architecture and implementation of at least one mainstream machine learning framework (TensorFlow/PyTorch/MXNet).

Preferred Qualifications

• Good knowledge in one of the following fields: Factorization Machine, Uplift Modeling, Diffusion Models, or Reinforcement Learning.
• Basic understanding of large recommendation systems and ads serving system concepts.

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 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).

About TikTok

TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. With global headquarters in Los Angeles and Singapore, we also have 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. Our innovative product helps people authentically express themselves, discover, and connect. 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.