Research Engineer - TikTok Ads Core ML, Ranking

Responsibilities

TikTok Ads Core ML Team aims at creating automatic delivery products for the next generation and developing advertising as a global business, instead of just a monetization tool to consolidate the delivery funnel framework allowing multiple teams to iterate parallel.

We're looking for innovative Research Engineers focused on ML/RL/LLM or other relevant professional domains, to join our TikTok Ads Core ML Ranking team. Ads Core Ranking team specifically focuses on maximizing delivery system efficiency and revenue growth through state-of-the-art models and frameworks. Our research topics include but not limited to: Generative Retrieval and Large Recommendation Model, LLM-based Ranking Application, and Optimization of System Resource Allocation with ROI target.

As part of our team, you will be responsible for:
- Optimize efficiency across the entire advertising funnel, including Recall&Rough-sort, Fine-sort(CTR/CVR), format/creative personalization and system resource allocation.
- Research & develop a global advanced advertising delivery system through frontier technologies, including ML/DL, RL, LLM and also scaling law in ads recommendation.
- Design & Set up system framework and standard to continuously improve overall efficiency and meet different vertical business needs.
- Work with product and business teams from various scenarios with global impact.

All of our team effort, is to continuously pursue and establish a world-leading ranking model & framework that always benefits our collaborators, users and customers to get better returns.

Qualifications

Minimum Qualifications:
- BS/MS degree in Computer Science, Statistics, Operation Research, Applied Mathematics, Physics or similar quantitative fields/with related experience.
- Research/industry experience in one or more of the following areas: machine learning, deep learning, statistical models and applied mathematical methods etc.
- Solid programming skills, proficient in C/C++ and Python. Familiar with basic data structure and algorithms.
- Familiar with at least one mainstream machine learning programming framework (TensorFlow/PyTorch/MXNet).
- Familiarity with online experimentation and analytics. Familiarity with big data systems including Hadoop and Spark.
- Curiosity towards learning and applying new technologies.

Preferred Qualifications:
- Participation in national math/coding competitions (ACM/Hacker Cup/Hash Code/USACO/IOI/CCPC etc.)
- Paper publications/citations in NLP/CV/Recommender System(RecSys/KDD/ICML/CVPR/NeurIPs, etc.)
- Experience in LLM, reinforcement learning, transfer learning, and counter-factual optimization is a plus.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $162000 - $316800 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 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.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.

Responsibilities

Responsibilities

TikTok Ads Core ML Team aims at creating automatic delivery products for the next generation and developing advertising as a global business, instead of just a monetization tool to consolidate the delivery funnel framework allowing multiple teams to iterate parallel.

We're looking for innovative Research Engineers focused on ML/RL/LLM or other relevant professional domains, to join our TikTok Ads Core ML Ranking team. Ads Core Ranking team specifically focuses on maximizing delivery system efficiency and revenue growth through state-of-the-art models and frameworks. Our research topics include but not limited to: Generative Retrieval and Large Recommendation Model, LLM-based Ranking Application, and Optimization of System Resource Allocation with ROI target.

As part of our team, you will be responsible for:
- Optimize efficiency across the entire advertising funnel, including Recall&Rough-sort, Fine-sort(CTR/CVR), format/creative personalization and system resource allocation.
- Research & develop a global advanced advertising delivery system through frontier technologies, including ML/DL, RL, LLM and also scaling law in ads recommendation.
- Design & Set up system framework and standard to continuously improve overall efficiency and meet different vertical business needs.
- Work with product and business teams from various scenarios with global impact.

All of our team effort, is to continuously pursue and establish a world-leading ranking model & framework that always benefits our collaborators, users and customers to get better returns.

Qualifications

Qualifications

Minimum Qualifications:
- BS/MS degree in Computer Science, Statistics, Operation Research, Applied Mathematics, Physics or similar quantitative fields/with related experience.
- Research/industry experience in one or more of the following areas: machine learning, deep learning, statistical models and applied mathematical methods etc.
- Solid programming skills, proficient in C/C++ and Python. Familiar with basic data structure and algorithms.
- Familiar with at least one mainstream machine learning programming framework (TensorFlow/PyTorch/MXNet).
- Familiarity with online experimentation and analytics. Familiarity with big data systems including Hadoop and Spark.
- Curiosity towards learning and applying new technologies.

Preferred Qualifications:
- Participation in national math/coding competitions (ACM/Hacker Cup/Hash Code/USACO/IOI/CCPC etc.)
- Paper publications/citations in NLP/CV/Recommender System(RecSys/KDD/ICML/CVPR/NeurIPs, etc.)
- Experience in LLM, reinforcement learning, transfer learning, and counter-factual optimization is a plus.