Staff Research Engineer, LLM - TikTok Ads Core ML, Ranking

es and research, including ML/DL, Reinforcement Learning, LLM, and scaling laws, within complex monetization scenarios.

• Optimize efficiency across the entire advertising funnel, covering Recall & Rough-sort, Fine-sort (CTR/CVR), format/creative personalization, and system resource allocation.
• Lead strategic initiatives and drive key projects by leveraging deep business acumen in monetization, ranking, search, and recommendation, ensuring precise technical decision-making.
• Establish and refine system frameworks and standards, continuously enhancing efficiency to meet diverse vertical business needs.
• Collaborate with product and business teams across global markets to maximize 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:

• MS or above degree in Computer Science, Statistics, Operation Research, Applied Mathematics, Physics or similar quantitative fields, with related experience in any of the following domains: search, ranking or recommendation.
• Hands-on experience in one or more of the following areas: machine learning, deep learning, statistical models and applied mathematical methods.
• Solid programming skills, proficient in C/C++ and Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.
• Familiarity with online experimentation and analytics.
• Familiarity with big data systems including Hadoop and Spark.
• Familiar with architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/Pytorch/MXNet).
• Curiosity towards new technologies and entrepreneurship.

Preferred Qualifications:

• Experience in reinforcement learning, transfer learning, and counter-factual optimization is a plus.
• Understanding of the business value of online advertising.
• Paper publications in NLP/CV/recommender system domain areas (such as, paper listing, workshop, oral on RecSys/KDD/ICML/NeurIPs/CVPR, etc. ).
• Experience in LLM is a plus.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $208800 - $438000 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.